Data science & ML platforms · C3.ai, Inc.

C3 AI

Enterprise AI platform for building and deploying large-scale predictive and generative AI applications.

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C3 AI is an enterprise platform built around an ontology layer that unifies data from disparate operational systems before applying machine learning and generative AI. It ships as the C3 Agentic AI Platform plus C3 AI Studio for development, C3 Generative AI for building on proprietary data, and a library of pre-built, industry-specific applications for use cases such as predictive maintenance, demand planning, and inventory optimization. It targets asset-heavy industries including manufacturing, utilities, oil and gas, and defense, where it is typically deployed by large enterprise or government customers alongside systems integration partners. It can be deployed on major public clouds or on-premises. No pricing is published; C3 AI engagements are sold through direct sales and typically involve significant implementation scope.

At a glance

Vendor C3.ai, Inc.
Pricing model Quote only
Free tier No
Deployment Cloud, Self-hosted
Open source No
Best for Large asset-heavy enterprises and government agencies needing industry-specific AI applications at scale.

Pricing

No published pricing; C3 AI is sold through direct enterprise sales engagements.

Pricing has not been verified yet — see the vendor's site.

Features

  • Ontology layer for unifying operational data
  • Low-code AI application development (C3 AI Studio)
  • Generative AI grounded in proprietary enterprise data
  • Pre-built industry applications (maintenance, demand planning, etc.)
  • Agent-based autonomous execution tooling
  • Multi-cloud and on-premises deployment

Integrations

Profile last reviewed September 21, 2026

Alternatives

DataRobot Enterprise AutoML and generative AI platform for building, deploying, and governing predictive models. Domino Data Lab Enterprise MLOps and data science platform for running, governing, and scaling model workflows across teams. Dataiku Collaborative platform spanning data preparation and machine learning, used by both analysts and data scientists.

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Terms to know

Machine learning Building models that learn patterns from data to make predictions or decisions, rather than following hand-coded rules. Predictive analytics Analytics that uses historical data and statistical models to estimate what is likely to happen next. Prescriptive analytics Analytics that recommends specific actions by combining predictions with optimization or decision rules. Predictive maintenance Using sensor data and models to predict when equipment is likely to fail so it can be serviced before it breaks down.

Related guides

How to choose a data science & ML platform The decisions that matter are who builds the models, how automated the modeling should be, and whether you want a cloud-native platform or a portable one.