C3.ai, Inc. (AI) Business

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ITEM 1. BUSINESS

Overview

C3 AI is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating Enterprise AI applications; C3 AI Applications, a portfolio of industry-specific Enterprise AI applications that enable the digital transformation of organizations globally; and C3 Generative AI — library of agentic AI applications to retrieve data, analyze information, surface insights, and orchestrate workflows to drive business value.

The C3 Agentic AI Platform and C3 AI Applications — built with our patented model-driven architecture — enable organizations to simplify and accelerate Enterprise AI application development, deployment, and administration. Our C3 AI software platform also enables developers to rapidly build applications without having to write complex, lengthy, structured programming code to define, control, and integrate the many requisite data and microservices components to work together; we significantly reduce the effort and complexity of the Enterprise AI software engineering problem.

Powered by C3 AI’s patented agent orchestration technology, C3 Generative AI enables autonomous agents to reflect, collaborate, and execute complex workflows — retrieving data, analyzing information, and delivering precise, actionable insights for high-value enterprise use cases across industries. C3 Generative AI delivers high-accuracy, domain-specific insights, and advanced reasoning across disparate enterprise and external data sources. C3 Generative AI is built natively into the C3 Agentic AI Platform and available with every C3 AI Application.

C3 Generative AI is also available as a standalone capability deployable against customer datasets and software applications enabling customers to leverage large language models (LLMs) and domain-specific agents to retrieve data, analyze information, surface insights, and orchestrate workflows to drive business value.

Enterprise AI Software Solutions

We have built a solution that enables our customers to rapidly develop, deploy, and operate large-scale Enterprise AI applications. Customers can deploy C3 AI software on major public cloud infrastructures, private cloud or hybrid environments, or directly on their servers and processors. We provide our customers and partners with an antidote to AI vendor lock-in.

We offer three primary families of software solutions, which we collectively refer to as our “C3 AI software”:

•The C3 Agentic AI Platform, our core technology, is a comprehensive, end-to-end application development and runtime environment that is designed to allow our customers to rapidly design, develop, and deploy Enterprise AI applications. The C3 Agentic AI Platform enables the creation of enterprise-grade AI agents that can autonomously perceive data, reason over complex systems, and take action to achieve defined business goals. These agents operate within secure, governed workflows and integrate seamlessly across the enterprise, delivering trusted, high-impact outcomes at scale.

•C3 AI Applications, built using the C3 Agentic AI Platform, is a portfolio of pre-built, extensible, industry-specific and application-specific SaaS Enterprise AI applications that can be rapidly installed and deployed.

•C3 Generative AI, combines the utility of LLMs, agentic AI, generative AI, reinforcement learning, natural language processing, and the C3 Agentic AI Platform to reflect, collaborate, and execute complex workflows.

C3 Agentic AI Platform

We believe the C3 Agentic AI Platform offers the only end-to-end platform-as-a-service that allows customers to rapidly design, develop, provision, and operate Enterprise AI applications at scale. Our customers can use the C3 Agentic AI Platform to build and operate their own custom Enterprise AI applications and to customize, operate, and manage C3 AI Applications.

The C3 Agentic AI Platform uses a patented model-driven architecture to accelerate delivery and reduce the complexities of developing Enterprise AI applications. The C3 AI model-driven architecture provides an “abstraction layer,” that allows developers to build Enterprise AI applications by using conceptual models of all the elements an application requires, instead of writing lengthy code. This provides significant benefits, including:

Scale AI Across the Business. Customers can use AI applications and models that optimize processes for every product, asset, customer, or transaction across all regions and businesses;

Deliver Results Faster. Customers can deploy AI applications and see results in one to two quarters and rapidly roll out additional applications and new capabilities;

Generate Meaningful Value. Customers can unlock sustained value, up to hundreds of millions to billions of dollars per year, from reduced costs, increased revenue, and higher margins; and

Govern AI with Confidence. Customers can ensure systematic, enterprise-wide governance of AI with our unified platform that offers data lineage and model governance.

The C3 Agentic AI Platform enables us and our customers to develop Enterprise AI applications by using conceptual models of all the elements required by the application — including data objects (e.g., customer, order, contract), computing resources (e.g., database, storage, messaging), data processing services (e.g., stream processing, batch processing), AI and ML services (e.g., model training, model pipeline management) — instead of having to write complex, lengthy code. This approach vastly reduces technical complexity for developers and the amount of code they need to write. The C3 Agentic AI Platform provides comprehensive capabilities to rapidly develop, deploy, and operate Enterprise AI applications at scale, including:

•Data Integration and Management Services. Services to readily ingest and aggregate massive volumes of diverse data from numerous internal and external sources and unify the data in a common and extensible data image.

•AI Application Development and Operationalization Services. Software services to explore data, build and train AI models, and operationalize AI models and applications at enterprise scale.

•Operational and Security Services. Cohesive core platform services (e.g., access control, data encryption, cybersecurity, time-series services, normalization, data privacy).

•C3 AI Studio. A low-code/no-code visual toolkit for developing, deploying, and operating Enterprise AI applications.

C3 AI Applications

C3 AI Applications is an expanding portfolio of turnkey and ready-to-use suite of Enterprise AI applications that address a range of high-value use cases. With C3 AI Applications, organizations can typically deploy enterprise-scale production AI applications in one to six months. Each of these applications is extensible and customizable to meet customer requirements.

C3 AI Asset Performance Suite

The C3 AI Asset Performance Suite drives enterprise asset performance, reduces downtime, and improves process efficiency. C3 AI customers use the C3 AI Asset Performance Suite to identify and predict asset performance risks, intervene before downtime occurs, and maximize asset performance.

The C3 AI Asset Performance Suite offers a flexible and scalable AI approach with better precision than alternatives. C3 AI’s value proposition within reliability emphasizes its (1) complementary approach to existing asset management and data historian systems, (2) detailed asset hierarchy modeling, including asset templates and failure mode libraries, (3) flexible AI pipelines that leverage best-in-class ML frameworks with AI explainability, and (4) comprehensive user workflows to action AI recommendations, with bidirectional integrations to work management and operations systems.

Three discrete applications comprise the C3 AI Asset Performance Suite:

•C3 AI Reliability increases operations, process, and equipment uptime by anticipating equipment risks and failures.

•C3 AI Process Optimization improves production rate and product quality with AI-optimized process control parameters in complex batch, semi-batch, or process manufacturing.

•C3 AI Energy Management helps operations teams achieve targets for energy cost, GHG emissions, water consumption, and waste reduction. The application models energy efficiency and emissions at every level of industrial processes from the individual equipment up to the facility as well as SKU-level product carbon footprints.

C3 AI Supply Chain Suite

The C3 AI Supply Chain Suite significantly improves supply chain resiliency and efficiency with proactive risk mitigation and advanced optimization. C3 AI’s value proposition in supply chain emphasizes its (1) strength in data unification for enterprise and external data to enable near-real-time global visibility of all goods, orders, and transportation, (2) detailed part-level tracking across the supply chain, (3) advanced AI to preemptively detect and mitigate risks, optimize processes, and avoid disruptions, and (4) fully complementary approach with enterprise resource planning, or ERP, systems (e.g., SAP ERP) and supply chain planning tools (e.g., SAP IBP, Logility).

Customers rely on the C3 AI Supply Chain Suite to rapidly improve business outcomes while providing flexibility in how they manage their entire supply chain software ecosystem. One large global manufacturing C3 AI customer uses C3 AI’s production scheduling software to support facilities using mainframe systems, continuing to use the same C3 AI Software while the underlying systems are upgraded to SAP ERP, highlighting the versatility and future-proofing of the model-driven architecture.

Five discrete applications comprise the C3 AI Supply Chain Suite:

•C3 AI Supply Network Risk identifies emerging inbound and outbound risks across the network.

•C3 AI Inventory Optimization analyzes variability across demand, supply, and production and optimizes inventory levels of all goods to eliminate excess inventory.

•C3 AI Demand Forecasting provides AI-based demand segmentation and granular, precision demand forecasts by capturing all high-value demand signals from enterprise and external data sources.

•C3 AI Production Schedule Optimization improves production efficiency using a holistic view of demand, supply, manufacturing, and distribution.

•C3 AI Sourcing Optimization reduces sourcing costs by detecting pricing anomalies and proactively monitoring all sourcing activity, based on feedback and other information provided from our customers.

C3 AI Defense & Intelligence Suite

C3 AI Defense & Intelligence Suite helps maximize mission capabilities. C3 AI customers span the U.S. Department of Defense, or the DoD, (including branches such as the U.S. Air Force), the Missile Defense Agency, and the DoD’s Chief Digital and Artificial Intelligence Office. C3 AI offers a core suite of products adaptable for each agency’s needs.

C3 AI differentiates on scalability of AI/ML and user workflows to solve critical missions. C3 AI’s defense & intelligence customers solve the following core needs with C3 AI: (1) rapid, multi-source data ingestion (e.g., structured, image, video, text), (2) efficient and scalable application of AI, ML, and deep learning techniques to provide novel insights, and (3) user-driven workflows that support investigative analyses, collaboration, and what-if scenario management.

Four core applications comprise the C3 AI Defense & Intelligence Suite:

•C3 AI Readiness, today configured across over 15 aircraft platforms, applies AI and advanced ML to help reduce unscheduled maintenance, preposition spare parts, and increase mission capability.

•C3 AI Intelligence Analysis accelerates investigative timelines with encrypted, obfuscated, federated search on people and relationships leveraging near real time, configurable machine learning pipelines for entities and sentiments.

•C3 AI Decision Advantage improves domain awareness and force management by synthesizing multiple intelligence sources in near real-time and enabling commanders and other decision makers with AI insights.

•C3 AI Contested Logistics ensures supply network resilience and availability in contested environments with extensive planning tools, near real-time monitoring and mission support, and AI assisted risk mitigation and contingency planning.

C3 AI State and Local Government Suite

The C3 AI State and Local Government Suite brings the power of Enterprise AI to state and local governments and law enforcement agencies, helping maximize tax revenues by providing highly precise property appraisals and enhancing public safety with AI-powered intelligence analysis.

For state, county and municipal law enforcement agencies:

•C3 Law Enforcement provides a single view for all relevant systems (e.g., jail records, license plate readers, record management, historical investigations), a natural language search interface to query for keywords across those sources, and an investigative visual graph network to explore connections, lowering the cost and time of criminal investigation.

For county property assessors and appraisers:

•C3 AI Residential Property Appraisal and C3 AI Commercial Property Appraisal provide data unification across numerous disparate systems and creates highly defensible property valuations, reducing the cost and time of real property appraisal.

For federal, state, and local governments:

•C3 Generative AI for Government Programs enables federal, state, and local government programs to help constituents retrieve immediate, accurate answers to any question across unique fields such as healthcare, transportation, benefits, public safety, legislature, and more.

•C3 Generative AI for Constituent Services accelerates response times from government offices to constituent inquiries by generating immediate and accurate responses. The application understands incoming inquiries and reviews the entire corpus of relevant data including benefit programs, government regulations, legislation, and federal grant websites to generate relevant and accurate responses in the tone and voice of each congressperson.

C3 AI Sustainability Suite

The C3 AI Sustainability Suite helps decrease greenhouse gas, or GHG, emissions, meet stakeholder and regulatory-specific environmental, social and governance, or ESG, expectations, and reduce energy costs, offering an alternative to existing reporting solutions and dramatically improving upon OEM-provided software (e.g., Siemens, Schneider) by using advanced AI and ML to reduce energy costs and GHG emissions.

Sustainability and energy management professionals struggle with three core challenges: (1) time-consuming, manual, and error-prone process to cobble together siloed data for ESG reporting, (2) an ever-evolving array of international reporting standards (e.g., CDP, GRI, SASB), and (3) forecasting ESG performance and managing goals (and individual projects) that are often outside of the ESG team’s capabilities. C3 AI Sustainability Suite solves these challenges and provides workflows and AI recommendations that enable teams and business units to collaborate on data unification across source systems, auto report generation aligned with major frameworks, and ESG forecasting and performance management.

Two applications comprise the C3 AI Sustainability Suite:

•C3 AI ESG lets companies measure, monitor, report, and improve their ESG performance, including scope 1, 2, and 3 emissions data.

C3 AI CRM Suite

C3 AI CRM adds to existing customer relationship management, or CRM, implementations with AI and delivers revenue-driving insights. C3 AI CRM does not replace existing CRM systems but significantly improves their utility. C3 AI CRM does not compete with core CRM systems (e.g., Salesforce); rather, it provides complementary AI-driven insights across revenue operations and intelligence and sales engagement. The application solves complex problems across bookings forecasting and opportunity scoring using differentiated capabilities to (1) integrate a comprehensive set of external data feeds (market data, news, firmographic information, etc.), (2) provide industry-specific data models, (3) apply best-in-class algorithms on each opportunity and stage, and (4) supports generative AI for enterprise search.

C3 AI Financial Services Suite

The C3 AI Financial Services Suite helps minimize compliance risks, improve balance attrition, increase customer satisfaction, reduce customer churn, identify fraud, and drive employee productivity with workflow-enabled AI applications. With flexible deployment options across public/private cloud or on-premise, its secure architecture, and open ML and AI framework, the C3 AI Financial Services Suite is uniquely positioned to drive significant business value for customers.

Three discrete applications comprise the C3 AI Financial Services Suite:

•C3 AI Anti-Money Laundering helps detect suspicious financial activity, identify fraudulent transactions, and flag bad actors with superior detection accuracy while reducing the false alerts for AML investigators.

•C3 AI Smart Lending drives productivity and customer satisfaction within the credit application and approval process, providing credit officers with contextualized insights that reduce processing timelines and increase approval precision.

•C3 AI Cash Management proactively monitors client treasury activity and preemptively predicts potential deposit churn to prevent balance attrition, helping increase customer retention and grow deposit balances.

C3 AI Health Suite

The C3 AI Health Suite helps to accelerate healthcare innovation, streamline drug development, boost manufacturing reliability and supply chain efficiency, enhance patient and provider experiences, simplify payment and reimbursement processes, and support data-driven commercial engagement.

•C3 AI Life Sciences Applications use AI at scale to provide actionable insights for critical challenges facing the industry. These applications drive efficiency by leveraging diverse data sets and applying a range of tuned ML models. These applications include: Research Analysis, Clinical Trial Management, Drug Development, Trial Protocol Design, Clinical Trial Management, Demand Forecasting, Marketing Claim and Collateral, Portfolio Optimization, Inventory Optimization, Regulatory Submissions, Patient Relationship Engagement, among others.

•C3 AI Applications for Healthcare leverages AI to improve health delivery efficiency by aggregating, validating, and communicating information broadly. These applications include: Clinical Trial Patient Matching, Early Chronic Disease Detection, Hospital Clinical Documentation, Clinical Workforce and Operating Room Optimization, Hospital Equipment Reliability, Patient Services Facilitation, Revenue Cycle Management Optimization, Payment Integrity, among others.

C3 Generative AI

Generative AI models have attracted significant attention in the last year due to capability improvements published by OpenAI, Google, Anthropic, Meta, Mistral, and others. These transformer-based models are proving valuable at parsing, understanding, and generating natural language, images, videos, and other forms of content. C3 AI is in a unique position to apply and augment these technologies to solve enterprise problems at scale.

The C3 Agentic AI Platform unifies omni-modal data — text, images telemetry, structured tables, etc. and offers all of the platform services necessary and sufficient for enterprise-class generative AI applications, including the services and pipelines to run, train, and host, and manage transformer AI models (or invoke externally managed models), and associated retriever models and other agents, tools, and pipelines.

C3 Generative AI helps users orchestrate AI agents to retrieve data, analyze information, surface insights, and initiate workflows for demanding, high value enterprise use cases that require accurate and reliable performance. C3 AI provides over 60 Generative AI applications across industries, business, and enterprise systems.

C3 Generative AI is a unified knowledge source that enables enterprise users to rapidly locate, retrieve, and act on enterprise data and insights through an intuitive search and chat interface. By combining state-of-the-art foundational large language models (LLMs), deep learning retrieval models, and the C3 Agentic AI Platform, C3 Generative AI provides deep domain support for information retrieval and reasoning across disparate datasets to improve decision making.

C3 Generative AI is built to support demanding enterprise requirements. By separating the LLM from enterprise data and leveraging retriever models together with enterprise-class AI agents and tools, C3 Generative AI provides deterministic responses with full traceability to the exact source, supports granular enterprise access control requirements, minimizes the risk of hallucination, reduces the risk of LLM-caused information leakage, and supports multiple LLM/foundation models.

C3 Generative AI is available with all C3 AI Applications to transform the human-computer interaction model between an end user and the underlying data and insights.

Customers also can use C3 Generative AI standalone, applied to their existing enterprise data sources, lakes, data warehouses, applications, and relevant external datasets. C3 Generative AI can be extended using the capabilities of the C3 Agentic AI Platform to meet complex enterprise requirements, allowing for the use of the natural language to perform tasks like invoking external APIs, running smaller AI/ML models, and initiating complex workflows.

We believe C3 Generative AI is unique in the market, offering:

•Omni-Modal Parsing, extracts high-quality content and metadata from wide array of unstructured formats — including presentations, spreadsheets, rich text, audio, and video — transforming them into a structured knowledge graph.

•Dynamic Planning Agent with Multi-Agent Collaboration allows the C3 AI’s planning agent to perform multi-step reasoning across all data types, coordinate with other agents to solve complex tasks and workflows.

•Easy Agent and Tool Authoring streamlines developer experience, enables users to rapidly create or enhance agents by integrating new tools in minutes, without the need for system upgrades.

•On-the-Fly Custom Visualizations generates context specific visualizations from natural language queries.

•Streamlined omni-modal data integration through a visual administrative interface, allowing queries across multiple sources such as Snowflake, Oracle, Databricks, and others, and documents in Amazon S3, Google Cloud, and others.

•Proprietary, fine-tuned foundation models for more capable, accurate, and faster structured data queries.

•Automatic support for questions and answers in over 130 languages.

•Dynamic configuration of LLMs and retrievers with no code, including automatic updates to related retrieval configurations, baseline prompts, and orchestration parameters.

•Advanced support for querying images and data tables embedded in documents.

•Enhanced accuracy with automated topic modeling and extraction of metadata from data contained in documents.

•Availability of all core product features in air-gapped environments.

•Advanced orchestration for complex queries involving multiple LLMs and retrieval tools.

•Improved C3 Generative AI co-pilot LLM to accelerate the productivity of developers and data scientists on the C3 Agentic AI Platform.

•Full extensibility to meet the unique requirement of the enterprise.

Lighthouse Customers

Historically, our market-entry strategy has been to establish high-value customer engagements with large global early adopters, or lighthouse customers, in Europe, Asia, and the United States across a range of industries. These lighthouse customers served as proof points for other potential customers in their particular industries. We have established intimate strategic relationships with our customers, including a number of large multinational corporations and government entities. We commonly enter into enterprise-wide agreements with entities that include multiple operating units or divisions. The core of this strategy has been to rapidly deliver high-value outcomes at large scale, across multiple industries, including financial services, manufacturing, defense, oil and gas, utilities, healthcare, and life sciences. We then use these use cases and outcomes to initiate discussions at numerous leading companies in each sector.

Consumption Pricing Model

In the first quarter of fiscal year 2023, we introduced a consumption-based pricing model to adapt to more challenging macro-economic conditions, and better meet the needs of customers. This has become common for enterprise software companies and is aligned with the models of some of our biggest partners, such as Google Cloud, Microsoft Azure, Amazon Web Services, or AWS, and Baker Hughes. With the consumption-based pricing model, customers either pay a monthly fee and consumption charges using vCPU and vGPU hours as the metric to calculate payment or enter into a time-certain multi-period commitment that may include consumption charges.

High-Value Outcomes

We are enabling the digital transformation of many of the world’s leading organizations and, in the process, helping them to attain short time-to-value and exceptionally high economic returns. At some companies, based on feedback and other information provided from our customers, we estimate our solutions have helped return billions of dollars in economic benefit.

Rapid Time to Value

The key to our market success and our primary competitive differentiator is our ability to leverage the C3 Agentic AI Platform and C3 AI Applications to bring high-value Enterprise AI applications into production use rapidly. We have deployed Enterprise AI applications into production use in as little as four weeks.

C3 AI Sales Cycle

Our typical sales cycle begins with one or more product and technical presentations about C3 AI, leading to a mapping of our capabilities to customer use cases. After mapping our capabilities to customer use cases, we typically sign a paid initial production deployment agreement (formerly referred to as “Pilots”) for the C3 Agentic AI Platform, a C3 AI Application, and C3 AI Center of Excellence (COE) including support services that lasts up to six months. During that period, we work with the customer to deploy a production-level C3 AI Application. After completing a successful initial production deployment, our customers will commonly continue to license the C3 AI Application and the C3 Agentic AI Platform for a consumption-based fee or enter into a time-certain multi-period commitment that may include consumption charges. Over time, our customers typically expand usage by adding users, expanding their use of the initial application to another use cases, purchasing additional C3 AI Applications for a subscription fee and by developing their own AI applications on the C3 Agentic AI Platform, which increases consumption-based fees as usage scales. Additionally, C3 AI can continue to support our customers as needed with our software and COE support services.

Partner Ecosystem

C3 AI’s Enterprise AI expertise and technology combined with our partners’ deep domain expertise enhances our solutions to joint customers. In fiscal year 2025, we made significant progress establishing and extending productive partnerships. Our partner ecosystem is increasingly effective at opening new doors with new customers and expanding product offerings with existing customers. In fiscal year 2025, we closed 192 agreements with and through our partner network, which includes Microsoft Azure, AWS, Google Cloud, McKinsey & Company, Baker Hughes, Booz Allen, and others.

C3 AI and Microsoft first partnered in 2018 to co-develop products and services for enterprise customers running on the Azure Infrastructure. The companies have collaborated to conduct co-marketing and co-selling strategies that rapidly scale distribution globally for their joint customers. For example, in the third quarter of fiscal year 2023, the companies collaborated to work with a global U.S. Energy company and a European technology company serving the construction and mining sectors and delivered a highly successful initial production deployment engagement to a large U.S. Defense Agency.

In September 2024, C3 AI and Microsoft Azure signed a new, multi-year global alliance agreement to accelerate growth in Enterprise AI. The renewed partnership deepens collaboration and joint investments across product innovation and integration, marketing and sales, and customer success initiatives, with a shared goal to accelerate the adoption of Enterprise AI on Azure across critical industries such as manufacturing, healthcare, energy, and defense.

C3 AI and Microsoft have aligned their global sales teams and field organizations to streamline enterprise engagements and quickly expand adoption, with the ability to transact C3 AI orders under Microsoft’s terms. This alignment enables joint account planning, co-selling, and coordinated industry outreach. C3 AI products are now integrated into Microsoft’s commercial marketplace incentive programs, allowing Azure sellers to receive quota retirement and compensation when transacting C3 AI solutions. All C3 AI Applications are available in the Azure Marketplace.

C3 AI and AWS first partnered in 2016, and during the third quarter of fiscal year 2023, we expanded and renewed our go-to-market partnership. In the third quarter of fiscal year 2023, AWS funded C3 AI to enhance C3 Law Enforcement optimized for AWS, integrating Amazon OpenSearch and AWS ML services to enhance the speed and quality of analysis for state and local agencies using the application on AWS.

In November 2023, C3 AI expanded its strategic collaboration agreement with AWS to deliver artificial intelligence solutions designed to solve customers’ critical business challenges across a variety of industries. In January 2025, C3 AI and AWS entered into a new multi-year strategic collaboration agreement with AWS to accelerate solution delivery and enhance go-to-market efforts.

C3 AI and Google Cloud initially partnered with C3 AI in 2021, and we expanded the partnership agreement in September 2022. The three-year agreement expands global joint selling activities and provides tighter integrations between C3 AI Applications and Google Cloud services. Under the terms of the partnership, the two companies are scaling their joint go-to-market strategy and expanding their joint customer initial production deployment programs with Fortune 2000 companies. Through this partnership, the team has identified a significant number of opportunities in the commercial and public sectors. All C3 AI Applications have been optimized to run in the Google Cloud Platform environment and are available in the Google Cloud Marketplace.

C3 AI and McKinsey & Company entered into a strategic collaboration agreement in January 2025 to accelerate Enterprise AI transformations at scale. The alliance combines the deep technical expertise of McKinsey’s AI practice, QuantumBlack, and its track record of deploying and scaling AI solutions across industries with C3 AI’s cutting-edge Enterprise AI software applications to help clients unlock the power of Enterprise AI and agentic AI to realize significant operational improvements and unlock new growth opportunities.

C3 AI and Booz Allen established a strategic partnership in fiscal year 2023 focused on providing strategic solutions into the government, defense, and intelligence sectors. C3 AI and Booz Allen are jointly going to market with the C3 Agentic AI Platform and suite of pre-built C3 AI Applications. Together the companies have trained employees on the C3 Agentic AI Platform and have closed multiple deals with the DoD’s Chief Digital and Artificial Intelligence Office and other organizations.

C3 AI and Baker Hughes, a leading oilfield industrial services, equipment, and digital services company, entered into a strategic collaboration in June 2019 to operate as the exclusive channel partner and reseller of C3 AI Software in the oil and gas industry and a non-exclusive reseller in other industries. As part of the original collaboration agreement, Baker Hughes made annual revenue commitments of $320 million over three years. The agreement was amended in June 2020 to extend the term of the agreement by two years and increase the revenue commitments to $450 million. The agreement was amended in October 2021 to extend the term of the agreement by one year and increase the total revenue commitments to $495 million. In January 2023, the companies substantially expanded their strategic partnership. The terms of this expansion resulted in an incremental C3 AI booking of $32.5 million, and the frequency of payments due from Baker Hughes was accelerated over the remaining term of the agreement. C3 AI agreed to provide additional products and services to Baker Hughes. The expanded agreement also provides Baker Hughes with a number of options to extend the term of the collaboration agreement beyond the initial five years.

In April 2025, the companies renewed and expanded their strategic partnership through a multi-year agreement, reinforcing their joint commitment to delivering enterprise-scale AI solutions across the energy sector. This collaboration focuses on deepening co-selling efforts, co-investment in AI solutions, and scaling deployments of joint solutions that are proven to improve production efficiency, reduce downtime, and increase operational visibility across assets in the world’s largest oil and gas companies.

As a result of our partnership with Baker Hughes, joint selling, and the credibility it has brought us in the market, C3 AI has closed several deals in the oil and gas and chemical industry, including LyondellBasell, Shell, ExxonMobil, Petronas, ENI, Aramco, LNG, ADNOC, PTTGC, Yokogawa, Braskem, and others.

C3 AI and Fractal first partnered in 2019, through the now-acquired Neal Analytics, and during the second quarter of fiscal year 2023, we significantly expanded our services and go-to-market partnership. The companies have collaborated to support customer service engagements, co-marketing campaigns, and co-selling activities. Fractal has committed to building a C3 AI practice deployment of C3 AI–trained engineers and data scientists. The companies have already collaborated on several successful customer engagements including implementing advanced metering infrastructure (AMI) at a Fortune 500 Utilities provider. In April 2025, C3 AI and Fractal expanded their agreement, continuing work with customers to implement, extend, and scale C3 AI solutions.

C3 AI and Paradyme first partnered in 2021, expanding the partnership during the third quarter of fiscal year 2024, and again in early 2025. The companies have collaborated to accelerate the delivery of AI applications for the U.S. Intelligence Community. The new agreements continue to expand the number of dedicated Paradyme staff to accelerate joint selling and delivery efforts.

C3 AI and Capgemini extended their partnership in November 2024 to advance Enterprise AI for business transformation. Capgemini will establish a dedicated global C3 AI practice to deliver scalable, rapid Enterprise AI solutions for joint clients across industries.

C3 AI and PwC entered into a strategic alliance in March 2025 to deploy AI-powered business transformation at enterprise-scale across industries. The alliance brings together PwC’s consulting and implementation capabilities with C3 AI’s prebuilt AI applications to help organizations in sectors like manufacturing, energy, and financial services rapidly deploy AI solutions.

C3 AI and Cognizant entered into a strategic alliance in April 2025 to deploy and scale Enterprise AI across industries, with an initial focus on healthcare and financial services.

Sales Model

Our sales organization is organized both geographically and in vertical market sales units that cooperate to sell to and service customers. We have a highly leveraged go-to-market model comprised of a global field sales force combined with significant alliance partnerships. Each of our strategic partners — including Microsoft, AWS, Google Cloud, McKinsey & Company, and Baker Hughes — has a large installed customer base with strong, established relationships, and a large global sales force that vastly extends our market coverage. We form specific sales targets and goals with each partner, enabling us to quickly and efficiently engage in customer accounts.

Early on, we focused on the oil and gas, federal, aerospace and defense, energy and utilities, manufacturing, and financial services sectors, as those industries were early adopters in Enterprise AI. We have since expanded into state and local governments, agriculture, food processing and consumer packaged goods, professional services, telecommunications, and hospitals and healthcare and are seeing increased industry diversity in our sales pipeline and initial production deployment engagements. Our goal is to rapidly move down-market in the coming years to serve the small and medium business segments of each industry.

Revenue Model

Our revenue consists of software subscription and professional services revenue. The substantial majority of our revenue is generated from subscriptions to our software.

Subscriptions

Our subscription revenue is primarily comprised of software licenses, software-as-a-service offerings, stand-ready COE support services, initial production deployments of our C3 AI Applications or Generative AI, and runtime and hosting fees. Licensing of our software grants our customers the right to use our software, either on their own cloud instance or their internal hardware infrastructure, over the contractual term. We offer a premium stand-ready service through our COE. Sales of our software-as-a-service offerings include a right to use our software over the contractual term. Customers pay a usage-based runtime fee for our C3 AI Software for specified levels of capacity. Our subscriptions also include our maintenance and support services, which include critical and continuous updates to the software that are integral to maintaining the intended utility of the software over the contractual term. We also provide software licenses that do not require maintenance and support services, for which revenue is recognized when the control of the software is transferred to the customer.

Within subscription revenue, we include revenue from contracts with customers that are based on our consumption-based pricing model. This model typically begins with a paid “Initial Production Deployment” phase of generally up-to six months that may include developer access to the C3 Agentic AI Platform, one or more C3 AI Applications or C3 Generative AI and COE support services with typically unlimited runtime. Following the initial production deployment period, customers either pay a monthly fee and consumption charges using vCPU and vGPU hours as the metric to calculate payment or enter into a time-certain multi-period commitment that may include consumption charges. We also charge the customer any hosting fees incurred by us for hosting in our own cloud instance.

Professional Services

Our professional services primarily include prioritized engineering services, paid implementation services, consulting and training. We maintain a professional services organization that offers resources, methodologies, and experience to help customers develop and deploy enterprise-scale AI applications. Our services are complemented by those of our partners. Our professional services strategy is to quickly train our customers to develop, customize, and deploy applications independently of us, rapidly making them self-sufficient.

Prioritized engineering services are undertaken at the request of customers to accelerate the development of software features in C3 AI Software products.

C3 AI consulting and implementation services help ensure successful customer outcomes throughout the application development and deployment phases, including setup and configuration, ML model development and tuning, and integration of multiple complex source systems.

In instances where a large or continuing professional services presence may be desired or necessary, we generally rely upon our partner ecosystem to provide those services. This enables us to maintain high gross margins and allows us the flexibility to rapidly deploy trained professional services personnel at large scale any place on the planet.

Marketing

Our multichannel marketing function is focused on market education, thought leadership, account-based marketing, and demand generation. We engage the market through digital, print, and social media, virtual and physical events, including C3 Transform, our annual international user, executive, and AI thought leadership conference, and other livestreamed events featuring C3 AI customers, C3 AI partners, and C3 AI experts in AI, ML, and data science. Our Chief Executive Officer, Tom Siebel — a recognized technology thought leader and author of the 2019 Wall Street Journal best seller, Digital Transformation: Survive and Thrive in an Era of Mass Extinction — is a frequent industry keynote speaker and is often interviewed by leading media, including The Wall Street Journal, The Financial Times, The Economist, Fortune, Forbes, CNBC, BloombergTV, and Yahoo! Finance.

Rich Human Capital

Our strongest asset is unquestionably the human capital that we have been able to attract, retain, and motivate. We have won the Glassdoor Best Place to Work award, were named a Battery Ventures/Glassdoor Highest-Rated Cloud Companies to Work For. We attract exceptionally talented, highly educated, experienced, motivated employees.

We have built a culture of high performance based on four core values:

•Drive and Innovation Propelling Growth. We self-select for people who love to work hard, think with rigor, speak with purpose, and act to achieve great things.

•Natural Curiosity to Solve the Impossible. We are self-learners, always seeking knowledge to accelerate innovation.

•Professional Integrity Governing All Endeavors. We comport ourselves with unwavering ethical integrity, respect, and courtesy.

•Collective Intelligence. We believe the unity of our team is substantially greater than the sum of its parts.

As of April 30, 2025, we had 1,181 full-time employees, with 933 based in the United States and 248 in our international locations.

Our Culture of High Performance

We are dedicated to achieving our mission to accelerate digital transformation of organizations globally by enabling the deployment of Enterprise AI at scale. Our people are domain experts in their respective fields. We are individuals with exceptional education and professional backgrounds. We are uncompromising in the quality of our work product. We build relationships with our customers grounded upon the highest levels of business ethics and professionalism, with a laser focus on customer success. We execute with precision.

Recognized Enterprise AI Industry Leadership

We believe we are broadly recognized as a leader in Enterprise AI with many other industry recognitions, including Fortune 50 AI Innovators (2023), CNBC Disruptor 50 (2020, 2019, 2018), BloombergNEF Pioneer (2020), Forbes Cloud 100 (2020, 2019, 2018, 2017), The Financial Times’ The Americas’ Fastest Growing Companies (2025, 2024, 2023, 2022, 2021), Deloitte Technology Fast 500 (2019), and EY Entrepreneur of the Year (2018, 2017) and have been named to the Constellation ShortListTM for Cloud-Based Data Science & Machine Learning Platforms (2025), the Constellation ShortListTM for Cloud-Based Data Science & Machine Learning Platforms (2024), Constellation ShortList™ for Artificial Intelligence & Machine Learning Cloud Platforms (2024, 2023, 2022, 2020), Constellation ShortList™ for Artificial Intelligence & Machine Learning best-of-Breed Platforms (2024), a Leader in the Forrester WaveTM: AI/ML Platforms (Q3 2024 and Q3 2022), and Forrester Wave: Industrial IoT Software Platforms (2019, 2018), and IDC MarketScape: Solutions for Industrial Platforms and Applications in Energy (2021).

Additionally, our customers have been recognized for their leadership in innovation across multiple industries:

•Georgia-Pacific was named the overall winner in the IDC’s Future Enterprise Best in Future of Operations North America Awards (2023) for its enterprise AI program to improve reliability for its manufacturing operations. Using C3 AI Reliability, the paper product producer and manufacturer can predict a failure, hours, days, or even weeks before it happens, avoiding unplanned downtime and significant impacts to revenue and customer order delivery.

•Roche was named the winner in the category of Operational Risk Management in the Verdantix 2023 EHS Innovation Excellence Awards Americas for harnessing AI and machine learning to resolve complex problems, resulting in improved safety, asset reliability, production and cost management.

•Baker Hughes was named a winner in the Constellation Research 13th Annual SuperNova Awards (2023) in the category of ESG & Sustainability for its work using AI to develop a more efficient, strategic ESG stakeholder materiality assessment process. Using C3 AI ESG, the company was able to design an intelligent ESG assessment process and used the resulting AI analyses to advise the development of a sustainability strategy geared towards catalyzing opportunity and buffering risk by focusing on the areas that matter. These insights help the team transition time spent from manually monitoring reams of data sources to driving strategic initiatives that improve ESG performance.

•The San Mateo County Sheriff’s Office was named a winner in the IDC Government Insights’ sixth annual Smart Cities North America Awards (2023) in the category of data-driven policing for implementing C3 Law Enforcement for analytics-powered public safety.

•Con Edison’s work with C3 AI was recognized in the IDC Future Enterprise Best in Future of Intelligence North America Awards (2022).

•The U.S. Air Force’s use of the C3 AI Readiness solution as a platform of choice was recognized in the Constellation SuperNova Awards (2021).

Sustainable Competitive Advantage: C3 AI Model-Driven Architecture

Our core technology is a cohesive family of integrated software services developed over a decade, engineered with a proprietary model-driven architecture, that provides all the software services and microservices necessary and sufficient to rapidly develop and deploy Enterprise AI applications.

AI applications developed with the C3 Agentic AI Platform can leverage any open-source software solutions and all of the cloud services of AWS, Microsoft Azure, Google Cloud, and can operate on any of these cloud platforms, on-premises, or in a hybrid cloud.

Compared to the structured programming approach that most organizations typically attempt, our model-driven architecture with declarative programming accelerates development by a factor of 26, while reducing the amount of code that must be written by up to 99%.

The big data and application demands of enterprise-scale AI applications require numerous underlying interdependent elements. These include enterprise data, extraprise data, sensor data, data persistence services, data streaming services, messaging services, analytics services, ML services, security services, data visualization, application development services, application monitoring services, and scores to hundreds more. With a traditional structured programming approach, developers spend significant time and effort to write extensive code to define, manage, connect, and control each element. This often results in overwhelming complexity and highly brittle applications that can break any time an underlying element is changed or updated — we believe this is a primary reason why the vast majority of AI efforts have not been deployed into production at enterprise scale.

By contrast, our model-driven architecture provides an abstraction layer, that allows our partners and our customers, as well as our internal C3 AI developers, to build or customize Enterprise AI applications by using conceptual models of all the elements an application requires. C3 AI provides a library of tens of thousands of prebuilt conceptual models that can be easily modified and extended, and developers can efficiently create their own models as well. These prebuilt, extensible models encompass a vast range of business objects (e.g., customer, order, contract), physical systems and subsystems (e.g., engine, boiler, chiller, compressor), computing resources and services (e.g., database, stream processing) — virtually anything an application requires can be represented as a model in our model-driven architecture. To ensure ongoing operability of our thousands of prebuilt and extensible models on different underlying infrastructure (e.g., AWS, Google Cloud, Microsoft Azure), our automated testing continuously executes approximately 60,000 tests and security scans with each change or update we make to our software or infrastructure.

Leveraging this model-driven architecture, application developers and data scientists can focus on delivering immediate value, without the need to manage the complex interdependencies of the underlying elements. These conceptual models can be reused by many applications, thereby accelerating development of new applications.

We believe our model-driven architecture and declarative programming approach provides significant competitive advantage both by enabling our customers and partners to successfully develop and deploy Enterprise AI applications faster, and by providing the foundation for C3 AI to rapidly extend our portfolio of cross-industry and industry-specific applications.

Strategic Competitive IP Advantage

We enjoy a rich patent portfolio that is a substantial competitive advantage, both offensive and defensive, in the Enterprise AI market - most notably, U.S. patents (No. 10,817,530, No. 10,824,634 and No. 11,954,112) which were granted for systems and methods for data processing and enterprise AI applications. C3 AI was also awarded a foundational U.S. patent (US 12,111,859) for generative AI agents. Key patented technologies include AI Orchestrator, Autonomy, Multimodal Model Integration, Natural Language Summarization, and Traceability and Security.

Our patent portfolio covers the key capabilities of our model-driven architecture that are the foundation of our highly differentiated technology. This includes methods, systems, and devices for data aggregation and unification, times-series data processing, data abstraction, ML implementation, generative AI and much more.

As of April 30, 2025, our technology is protected by a broad patent portfolio, with 35 issued patents in the United States, 30 issued counterpart patents in a number of international jurisdictions, over 60 patent applications pending in the United States, and 104 patent applications pending internationally. Our issued patents expire beginning in 2033 through 2043. We continually review our development efforts to assess the existence and patentability of new intellectual property.

Intellectual property is important to the success of our business. We rely on a combination of patent, copyright, trademark, and trade secret laws in the United States and other jurisdictions, as well as license agreements, confidentiality procedures, non-disclosure agreements with third parties, and other contractual protections, to protect our intellectual property rights, including our proprietary technology, software, know-how, and brand. However, we believe that factors such as the technological and creative skills of our personnel, creation of new services, features and functionality, and frequent enhancements to our platform are more essential to establishing and maintaining our technology leadership position. See the section titled “Risk Factors - Risks Related to Our Intellectual Property” in Part I, Item 1A in this Annual Report on Form 10-K for a discussion of the risks associated with our intellectual property.

The C3 AI Model-Driven Architecture

Over the last four decades, the information technology industry has grown from about $120 billion globally in 1980 to almost $8.0 trillion today. During this time, the IT industry has transitioned from mainframe computing to handheld computing. The software industry has transitioned from custom applications based on mainframe standards to applications developed on a relational database foundation, to enterprise application software, to SaaS and mobile apps, and now to the AI-enabled enterprise.

The challenges that must be addressed to enable today’s Enterprise AI applications are nontrivial, as are the array of capabilities and services necessary for building and operating these applications at scale. To develop an effective Enterprise AI application, it is necessary to ingest and aggregate data from a variety of enterprise information systems, sensors, markets, and products to provide a complete view of the enterprise. In addition, the data need to be processed at the rate they arrive, in a highly secure and resilient system that addresses persistence, event processing, ML, and visualization. This requires a massive, horizontally scalable elastic distributed processing capability offered only by modern cloud platforms and supercomputer systems. The resultant data persistence requirements are staggering.

To understand this challenge, consider just a few of the requirements needed to support Enterprise AI applications:

•Data Integration. A prerequisite to AI at industrial scale is the availability of a unified, federated image of all the data contained in the multitude of (1) internal data, including enterprise information systems (e.g., ERP, CRM, SCADA, HR, MRP) and sensor IoT networks; and (2) external data, including weather, terrain, satellite imagery, social media, trade data, biometrics, pricing, and market data.

•Data Persistence. The data aggregated and processed includes every type of structured and unstructured data imaginable, including personally identifiable information, images, text, video, telemetry, voice, and network topologies. As there is no one size fits all database optimized for all these data types, there is a need for a multiple database technologies.

•Platform Services. A myriad of sophisticated platform services are necessary for any Enterprise AI or IoT application. Examples include access control, data encryption in motion, encryption at rest, ETL, queuing, pipeline management, autoscaling, multitenancy, authentication, authorization, cybersecurity, time-series services, normalization, data privacy, GDPR privacy compliance, NERC-CIP compliance, and SOC2 compliance.

•Analytics Processing. The volumes and velocity of data acquisition in such systems are blinding and the types of data and analytics requirements are highly divergent, requiring a range of analytics processing services. These include continuous analytics processing, MapReduce, batch processing, stream processing, and recursive processing.

•Machine Learning Services. The whole point of these systems is to enable data scientists to develop and deploy ML models. There is a range of tools necessary to enable that, including Jupyter Notebooks, R Studio, Azure ML, Amazon Sagemaker, and Google Vertex AI. Increasingly important is an extensible curation of ML libraries such as PyTorch, TensorFlow, Keras, Hugging Face transformers, and XGBoost. An effective AI and IoT platform needs to support them all.

•Data Visualization Tools. Any viable AI architecture needs to enable a rich and varied set of data visualization tools including Microsoft Power BI, Google Data Studio, Looker, Tableau, and others.

•Developer Tools and UI Frameworks. An organization’s IT development and data science teams each have adopted and become comfortable with a set of application development frameworks and user interface development tools. An AI and IoT platform must support all of these tools — including Visual Studio, Jupyter Lab, JetBrains IDEs, React, Angular, and VueJS — or it will be rejected as unusable by the IT development teams.

•Open, Extensible, Future-Proof. The current pace of software and algorithm innovation is accelerating. An AI and IoT platform architecture must provide the capability to replace any components with next-generation improvements; in the era of generative AI, that means the constant stream of newly released and ever-more-powerful LLMs. Moreover, the platform must enable the incorporation of any new open source or proprietary software innovations without adversely affecting the functionality or performance of an organization’s existing applications. This is a level-zero requirement.

The C3 Agentic AI Platform — built with model-driven architecture — has been refined, tested, and proven in some of the most demanding industries and production environments from electric utilities and manufacturing to oil and gas and defense, comprising petabyte-scale datasets from thousands of vastly disparate source systems, massive volumes of high-frequency time series data from millions of devices, and hundreds of thousands of ML models.

Awash in “AI Platforms”

Today the market is awash in AI solutions that provide component parts to design, develop, provision, and operate Enterprise AI applications, including Cassandra, Cloudera, DataStax, AWS IoT, and Hadoop. AWS, Microsoft Azure, and Google Cloud each offer an elastic cloud computing platform and an increasingly innovative library of microservices that can be used for data aggregation, ETL, queuing, data streaming, MapReduce, continuous analytics processing, ML services, and data visualization. An array of open source software offerings cater to data management, machine learning services, and analytics. While these products are useful, we believe that none offers the scope of utility necessary and sufficient to rapidly design, develop and deploy Enterprise AI applications.

“Do It Yourself” Enterprise AI?

Software innovation cycles follow a typical pattern. Early in the cycle, companies often take a do-it-yourself approach and try building the new technology themselves. Just as happened with the introduction of ERP and CRM software in prior innovation cycles, the initial reaction of many IT organizations is to try to internally develop a general-purpose Enterprise AI and IoT platform, using open source software with a combination of microservices from cloud providers like AWS and Google Cloud.

The process starts by taking some subset of myriad proprietary and open source solutions and organizing them into a platform architecture. The next step is to assemble hundreds to thousands of programmers, frequently distributed around the world, using structured programming and application programming interfaces, or APIs, to attempt to stitch these various programs, data sources, sensors, ML models, development tools, and user interface paradigms together into a unified, functional, seamless whole that will enable the organization to excel at designing, developing, provisioning, and deploying numerous enterprise scale AI and IoT applications.

The complexity of such a system is much greater than developing a CRM or ERP system. There are a number of problems with this approach:

•Complexity. Using structured programming, the number of software API connections that one needs to establish, harden, test, and verify for a complex system can, in our estimation, approach the order of 1013. The developers of the system need to individually and collectively grasp that level of complexity to get it to work. We believe the number of programmers capable of dealing with that level of complexity is quite small.

Aside from the platform developers, the application developers and data scientists also need to understand the complexity of the architecture and all the underlying data and process dependencies in order to develop any application.

•Brittleness. Spaghetti-code applications of this nature are highly dependent upon each and every component working properly. If one developer introduces a bug into any one of the open source components, all applications developed with that platform may cease to function.

•Future Proof. As new libraries, faster databases, and new ML techniques become available, those new utilities need to be available within the platform. Consequently, every application that was built on the platform will likely need to be reprogrammed in order to function correctly. This may take months to years.

•Data Integration. An integrated, federated common object data model is absolutely necessary for this application domain. Using this type of structured programming, API-driven architecture may require hundreds of person-years to develop an integrated data model for any large corporation. This is the primary reason why tens to hundreds of millions of dollars are spent, and several years later, no applications are deployed. The Fortune 500 is littered with such disaster stories.

The C3 Agentic AI Platform: Model-Driven Architecture

The notion of a model-driven architecture was developed at the beginning of the 21st century in response to the growing complexity of enterprise application development requirements. Although structured programming remains the state of the art for many applications today, it breaks down with the complexity and scale required for modern Enterprise AI and IoT applications, resulting in a Gordian knot. Model-driven architecture provides the knife to cut the Gordian knot of structured programming for highly complex problems. The C3 Agentic AI Platform is designed and built with a model-driven architecture.

Central to a model-driven architecture is the concept of a “model” that serves as an abstraction layer to simplify the programming problem. Using models, the programmer or application developer does not have to be concerned with all the data types, data interconnections, and processes that act on the data associated with any given entity, e.g., customer, tractor, doctor, or fuel type. He or she simply needs to address the model for any given entity, e.g., customer, and all the underlying data, data interrelationships, pointers, APIs, associations, connections, and processes associated with or used to manipulate those data are abstracted in the model itself.

Using the C3 Agentic AI Platform and its model-driven architecture, virtually anything can be represented as a model - even, for example, applications, including databases, natural language processing engines, and image recognition systems. Models also support a concept called inheritance. An AI application built with the C3 Agentic AI Platform might include a model called relational database, that in turn serves as a placeholder that might incorporate any relational database system like Oracle, Postgres, Aurora, Spanner, or SQL Server. A key-value store model might contain Cassandra, HBase, Cosmos DB, or DynamoDB.

The C3 Agentic AI Platform and its application components deliver rich, workflow-enabled AI solutions built on a robust application platform featuring advanced data fusion, governance, and scalable AI/ML operations. Unlike legacy stacks that bolt on AI capabilities, the C3 Agentic AI Platform has been purpose-built and refined over 15 years to rapidly develop and deploy enterprise-grade AI applications. We leverage the full AI technology stack—including silicon, cloud infrastructure services, and foundation models—to ensure performance and flexibility.

C3 AI Reduces Complexity, Simplifies Development

With its model-driven architecture, the C3 Agentic AI Platform provides an abstraction layer and semantics to represent the application. This frees the programmer from having to worry about data mapping, API syntax, and the mechanics of myriad computational processes including ETL, queuing, pipeline management, and encryption.

The optimal design for an object model to address Enterprise AI and IoT applications uses abstract models as placeholders to which a programmer can link an appropriate application. The relational database model might link to Postgres. A report writer model might link to MicroStrategy. A data visualization model might link to Tableau. And so on. A powerful feature of a model-driven architecture is that as new open source or proprietary solutions become available, the object model library can simply be extended to incorporate that new feature.

Another important capability of the C3 Agentic AI Platform enabled by its model-driven architecture is that the applications developed on the platform are future-proofed: due to the modular nature of the model-driven architecture, new, upgraded, or enhanced services can be easily integrated with the C3 Agentic AI Platform. This enables organizations to immediately and easily take advantage of new and improved product offerings as they become available.

Platform Independence: Multi-Cloud and Polyglot Cloud Deployment

Enterprises today often have a multi-cloud strategy. While corporate leaders are eagerly embracing the cloud, they are also very concerned about cloud vendor lock-in. They want to be able to continually negotiate. They want to deploy different applications in clouds from different vendors, and they want to be free to move applications from one cloud vendor to another.

Multi-cloud deployment is therefore an additional requirement of a modern model-driven software platform that is fully supported by the C3 Agentic AI Platform. Applications developed with the C3 Agentic AI Platform can run without modification on any cloud and on bare metal behind the firewall in a hybrid cloud environment.

A requirement for the new AI technology stack — that the C3 Agentic AI Platform delivers — is polyglot cloud deployment capability: the ability to mix various services from multiple cloud providers and to easily swap and replace those services. The cloud vendors provide the market a great service by enabling instant access to virtually unlimited horizontally scalable computing capacity and effectively infinite storage capacity at exceptionally low cost. As the cloud vendors aggressively compete with one another on price, the cost of cloud computing and storage is consistently decreasing.

C3 Agentic AI Platform: A Tested, Proven, and Patented AI Suite

The model-driven approach to developing Enterprise AI applications using the C3 Agentic AI Platform has been tested and proven in dozens of large-scale, real-world deployments at some of the world’s largest organizations.

C3 AI provides a powerful platform enabling these and other leading organizations to develop and operate Enterprise AI applications at scale, with a fraction of the effort and resources required by other approaches. Applications built with the C3 Agentic AI Platform are flexible, easily upgraded, and can be ported across different cloud platforms with little or no modification, providing a solution that future-proofs customers’ investment in Enterprise AI and IoT application development.

C3 AI was the first to file and receive a core patent for Agentic AI and its orchestration in enterprise applications. Our platform supports high-accuracy, omni-model agentic capabilities for retrieval, reasoning, and decision-making. A key innovation is our Dynamic Planning Agent, which enables multi-step data retrieval, reasoning, visualization, and the execution of actions across diverse data types. This agentic orchestration is powered by C3 AI’s metadata-based Object Models, which provide semantic understanding of enterprise data. Once data are integrated into C3 AI Objects, customers can utilize pre-built agents and tools to interact with the data, reason over it, and take informed action, or they can integrate their own agents and tools within our framework.

The platform is LLM-agnostic and seamlessly supports both commercial and open-source large language models (LLMs), offering customers the flexibility to choose models that best meet their needs.

Competition

Our main sources of current and potential competition fall into several categories:

•corporate IT organizations that attempt to develop internal solutions for their enterprises;

•commercial enterprise and point solution software providers;

•open-source software providers with data management, ML, and analytics offerings;

•public cloud providers offering discrete tools and micro-services with data management, ML, and analytics functionality;

•system integrators that develop and provide custom software solutions;

•legacy data management product providers; and

•strategic and technology partners who may also offer our competitors’ technology or otherwise partner with them, including our strategic partners who may offer a substantially similar solution based on a competitor’s technology or internally developed technology that is competitive with ours.

Our primary competition is largely do-it-yourself, custom-developed, company-specific AI platforms and applications developed by internal IT organizations. Such efforts usually involve the integration of internally developed tools, open source solutions, and point solutions offered by independent software vendors, and/or components offered in the AWS, Microsoft Azure, or Google Cloud platforms. Frequently these efforts will be managed as professional service projects by organizations like Accenture or Lockheed Martin. These tend to be very costly and time-consuming software engineering projects, often fail, and, if at all successful, usually require many years to realize economic return. Most of our customers have tried and failed at one or more such bespoke development efforts, sometimes at great expense, before turning to C3 AI for their AI solution.

We are unaware of any end-to-end Enterprise AI development platforms that are directly competitive with the C3 Agentic AI Platform. The commercial product offerings that were formerly positioned as functionally equivalent to C3 AI were GE Predix and IBM Watson, both multibillion-dollar software engineering efforts backed by massive promotional campaigns; we no longer encounter them in competitive situations.

Growth Strategy

We are investing in the expansion of our direct enterprise sales and service organization both geographically and across vertical markets to expand the use of C3 AI solutions within existing customers and establish new customer relationships.

The consumption-based pricing model helps us better meet the needs of our customers by making it easier and less costly to adopt our products and services. With the consumption-based pricing model, customers start with initial production deployments which are subscription for developers access to the C3 Agentic AI Platform and/or C3 AI Application or C3 Generative AI and COE support services of up to six-months. After completing a successful initial production deployment, our customers may continue to license the C3 AI Application and the C3 Agentic AI Platform for a consumption-based fee or enter into a time-certain multi-period commitment that may include consumption charges.

After we help our customers solve their initial use cases, they frequently identify incremental opportunities within their operations and expand their use of our products. The increased engagement is measured by a combination of increased vCPU/vGPU usage, increased C3 AI Software subscriptions and subscriptions to the C3 Agentic AI Platform for in-house AI application development.

We are focusing on certain markets and verticals that provide us substantial growth opportunities and demand for our products, such as the federal, defense and aerospace industry and the state and local industry.

Our release of the C3 Generative AI solutions in March 2023 is receiving considerable interest, and is a key part of our growth strategy. We closed 13 agreements for C3 Generative AI in the fourth quarter of fiscal year 2024 with large enterprises, and are working through a substantial pipeline of C3 Generative AI opportunities. The C3 AI generative application is available on both AWS Marketplace and the Google Cloud Marketplace.

We continue to invest heavily in research and development to maintain technology leadership. Our product roadmap includes a wide range of new functions and products to be released in the coming years that we expect to contribute to revenue growth with both new and existing customers.

The Evolution of C3 AI

Like many of the world’s leading technology companies, C3 AI has changed and expanded its branding and product portfolios to achieve market leadership.

In January of 2009, we founded C3, Inc with the purpose of developing and marketing a software platform and family of software products that would enable companies to exploit the power of elastic cloud computing, big data, IoT, and predictive analytics.

When we founded C3 AI, we believed the market for elastic cloud computing, IoT, big data, and predictive analytics software was destined to be large. That proved true. However, in 2009 the market was nascent, and the specific applications and markets were unknown. Based on Forrester’s report on the Public Cloud Market Outlook, in 2008, the global public cloud market was less than $20 billion; in 2023, it was expected to approach $500 billion. In 2008, there were less than 1 billion IoT devices worldwide;1 in 2023, that number was expected to exceed 55 billion based on the IDC report published in 2023. In 2008, AI software - as we think about it today - did not exist. This year the AI software market is expected to exceed $450 billion based on the IDC report. We believe that by any standard that constitutes explosive growth.

When we consider mega-market developments like the internet, the smartphone, and AI, it is impossible to anticipate a priori exactly how these markets will develop. With the advent of the Mosaic internet browser in 1993, who could have anticipated Amazon and Google? With the founding of Apple Computer Company in 1976, who could have anticipated the iPhone? The Apple Store? Apple TV? iTunes? These mega-markets develop in unanticipated ways.

1 https://www.statista.com/statistics/764026/number-of-iot-devices-in-use-worldwide/

We believe that Enterprise AI is a mega-market event. As this market has developed, C3 AI has done a fine job of continually expanding its market offerings and continually expanding its market position to address the ever-expanding opportunity.

C3: 2009 - 2012

We founded C3 in January of 2009 and developed some of the core components of what is now the C3 AI Platform within the first year. There was much discussion and interest in the 2008 – 2011 timeframe about what we now consider sustainability initiatives, including clean tech, energy management, LEED certification, and cap and trade vs. carbon offsets; and as a result, we decided to focus our first use case on energy management. That proved to be a good decision.

In 2010 we released our first product, C3 Energy Management.

From 2010 – 2012, we closed several large agreements with a large global industrial company, one of the world’s largest chemical companies, two large utilities, and one of the world’s largest high-tech companies.

C3 Energy: 2013-2015

In 2012, C3 engaged McKinsey & Co. to conduct a study and make recommendations for maximizing growth including optimal company positioning and an associated pricing and product strategy. In the first two decades of the 21st century, utility companies were in the process of spending $2 trillion globally to upgrade their grid infrastructures with IoT devices, enabling the advent of the smart grid. Utilities were early adopters of IoT.

The McKinsey analysis recommended that there was a significant opportunity for C3 to expand its business by applying its energy management and energy efficiency solutions to utilities at grid scale in addition to selling to enterprises.

Adopting the McKinsey recommendations, C3 expanded its market position, rebranded as C3 Energy, and in addition to its prior solutions, C3 Energy offered a family of predictive analytics solutions - which were reliant on emerging AI techniques including machine learning, supervised learning, and unsupervised learning. Built to address the utility value chains of power generation, transmission, distribution, and consumption, these solutions optimize the operation of large and complex power grid infrastructures. The C3 Energy utility software products expanded to include C3 AMI Operations, C3 Revenue Protection, C3 Predictive Analytics, C3 Revenue Production, and C3 Reliability.

Many customers also licensed our core C3 Platform that they could use to develop their own predictive analytics application and/or to develop derivative works of the C3 Energy applications.

It was during this period that the company formed its data science division to develop and apply AI techniques to our applications including machine learning, predictive analytics, supervised learning, and unsupervised learning.

During this period, the company began to offer its products to the oil and gas industry including its AI Predictive Maintenance application for oil pumps, offshore oil rigs, LNG production facilities, etc. The company continued to offer its products for energy management and energy efficiency to utility companies based on per customer pricing and to enterprises based on expected value pricing.

This expansion into energy markets proved successful as the company booked2 approximately $83 million in contracts and recognized $63.9 million in revenue during this period.

C3 IoT: 2016 – 2018

By 2016, we were seeing significant expansion in the cloud computing market and the proliferation of IoT sensors was expanding dramatically across many industries. We were increasingly approached by manufacturing companies, financial services companies, oil and gas companies, and the U.S. Department of Defense to deploy the same types of AI applications that we had successfully deployed in enterprises and utilities including AI Predictive Maintenance, AI Fraud Detection, AI Inventory Optimization, and C3 Energy Management.

2 Unaudited

At that time, the common expression for these types of applications was “IoT,” and we appropriately rebranded the company as C3 IoT to communicate to the market that we were again expanding our market offerings from primarily one vertical market (energy) to a broadening range of markets.

In response to this increased demand, the company tailored its core applications to meet the needs of those industries. As such, in addition to the C3 Platform, we offered market-specific versions of all our applications including AI Predictive Maintenance, AI Inventory Optimization, and AI Energy Management for the utility, oil and gas, defense, and financial services industries. In addition, the company introduced the concept of 4-to-16-week product trials as part of the sales process.

This market and product line expansion again proved successful as the company booked2 approximately $203 million in contracts and recognized $120.4 million in revenue from 2016 – 2018.

C3 AI: 2019 – Present

As the market for cloud computing, big data, IoT, and predictive analytics continued to expand, the market perception of IoT - as expressed in the literature, technical conferences, the academy, and in customer expectations - changed. While IoT had previously been considered at the confluence of sensor devices and AI applications, it was clear that IoT was becoming a concept increasingly centered on the devices - the IoT sensors themselves - with the AI applications considered a separate category. As this developed, the C3 IoT brand became confusing to the market, as many customers had the impression that the company was primarily in the business of manufacturing IoT sensors and devices.

To eliminate this market confusion, we rebranded the company C3 AI, clearly communicating that we were in the computer software business.

In addition to the products and services that the company offered since its inception, C3 AI again expanded its product offerings that now include over 165 AI production applications for the utility, oil & gas, state and local governments, financial services, manufacturing, health, and communications industries, and U.S. defense and intelligence sectors. Across industries, we introduced a number of AI application products that serve all vertical markets including C3 AI Ex Machina to address the needs of the growing citizen data science market, C3 AI CRM, C3 AI Data Vision, C3 AI ESG, and C3 Generative AI.

Again, this market expansion proved successful, enabling C3 AI to book2 over $1.8 billion in additional contracts and recognize $1.7 billion in revenue from 2019 – 2025.

C3 AI was well ahead of its time in predicting the scale of the opportunity in enterprise AI applications. We began when the market was nascent, and as the market has developed and expanded, we have expanded our branding and our market offerings to meet market expectations.

University Relations: C3.ai Digital Transformation Institute

Established in February 2020, the C3.ai Digital Transformation Institute, or C3.ai DTI, is a research consortium dedicated to accelerating the benefits of AI for business, government, and society. The goal of C3.ai DTI is to develop the field of Digital Transformation Science by leveraging laboratory and research facilities at UC Berkeley, UIUC, and consortium institutions. C3.ai DTI forms dynamic teams of the world's best researchers to interact with faculty and students to advance AI techniques for industrial, commercial, and public sector applications.

Government Regulation

Our business activities are subject to various federal, state, local, and foreign laws, rules, and regulations. Compliance with these laws, rules, and regulations has not had, and is not expected to have, a material effect on our capital expenditures, results of operations and competitive position as compared to prior periods. Nevertheless, compliance with existing or future governmental regulations, including, but not limited to, those pertaining to global trade, consumer and data protection, and taxes, could have a material impact on our business in subsequent periods. For more information on the potential impacts of government regulations affecting our business, see the section titled “Risk Factors” contained in Part I, Item 1A of this Annual Report on Form 10-K.

Available Information

Our website address is located at www.c3.ai, and our investor relations website is located at ir.c3.ai. We file electronically with the SEC our annual reports on Form 10-K, quarterly reports on Form 10-Q, current reports on Form 8-K, and amendments to those reports filed or furnished pursuant to Section 13(a) or 15(d) of the Exchange Act. We make available on our investor relations website, free of charge, copies of these reports and other information as soon as reasonably practicable after we electronically file such material with, or furnish it to, the SEC. These filings with the SEC are also available on the SEC’s website located at www.sec.gov.

We announce material information to the public through a variety of means, including filings with the SEC, press releases, public conference calls, our website (c3.ai), the investor relations section of our website (ir.c3.ai), X (formerly Twitter) (@C3_AI), and LinkedIn (@C3-AI-Enterprise-AI) accounts. We use these channels to communicate with investors and the public about our company, our products and services and other matters. Therefore, we encourage investors, the media and others interested in our company to review the information we make public in these locations, as such information could be deemed to be material information. Further, corporate governance information, including our corporate governance guidelines, code of business conduct and ethics, and committee charters, is also available on our investor relations website.

The content of or accessible through our websites or our social media channels are not incorporated by reference into this Annual Report on Form 10-K or in any other report or document we file with the SEC, and any references to our websites or social media channels are inactive textual references only.

C3.ai, Inc. (AI) Business

ITEM 1. BUSINESS

Overview

Enterprise AI Software Solutions

Table of Contents

C3 Agentic AI Platform

C3 AI Applications

C3 AI Asset Performance Suite

Table of Contents

•C3 AI Reliability increases operations, process, and equipment uptime by anticipating equipment risks and failures.

C3 AI Supply Chain Suite

•C3 AI Supply Network Risk identifies emerging inbound and outbound risks across the network.

C3 AI Defense & Intelligence Suite

Table of Contents

•C3 AI Contested Logistics ensures supply network resilience and availability in contested environments with extensive planning tools, near real-time monitoring and mission support, and AI assisted risk mitigation and contingency planning.

C3 AI State and Local Government Suite

C3 AI Sustainability Suite

Table of Contents

C3 AI CRM Suite

C3 AI Financial Services Suite

C3 AI Health Suite

C3 Generative AI

Table of Contents

Table of Contents

Lighthouse Customers

Consumption Pricing Model

High-Value Outcomes

Rapid Time to Value

C3 AI Sales Cycle

Partner Ecosystem

Table of Contents

Table of Contents

Sales Model

Table of Contents

Revenue Model

Subscriptions

Professional Services

Table of Contents

Marketing

Rich Human Capital

Our Culture of High Performance

Recognized Enterprise AI Industry Leadership

Table of Contents

Sustainable Competitive Advantage: C3 AI Model-Driven Architecture

Table of Contents

Strategic Competitive IP Advantage

The C3 AI Model-Driven Architecture

Table of Contents

Table of Contents

Awash in “AI Platforms”

“Do It Yourself” Enterprise AI?

Table of Contents

The C3 Agentic AI Platform: Model-Driven Architecture

C3 AI Reduces Complexity, Simplifies Development

Platform Independence: Multi-Cloud and Polyglot Cloud Deployment

Table of Contents

C3 Agentic AI Platform: A Tested, Proven, and Patented AI Suite

Competition

Table of Contents

Growth Strategy

The Evolution of C3 AI

Table of Contents

C3: 2009 - 2012

C3 Energy: 2013-2015

Many customers also licensed our core C3 Platform that they could use to develop their own predictive analytics application and/or to develop derivative works of the C3 Energy applications.

C3 IoT: 2016 – 2018

2 Unaudited

Table of Contents

C3 AI: 2019 – Present

University Relations: C3.ai Digital Transformation Institute

Government Regulation

Table of Contents

Available Information