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The Context Engine
for the AI Era

Data is everywhere — but users and AI work best with context. Credible brings shared meaning — definitions, institutional knowledge, and analytical intent —  into context, so analysis leads to clear decisions.

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1. Capture shared meaning

The meaning of your data is scattered — in schemas, queries, catalogs, and unstructured content. Credible captures this institutional knowledge directly from your data ecosystem, so it’s no longer implicit, siloed, and fragile.

2. Encode it in a semantic model

Credible AI helps you encode shared meaning into a semantic model. The model is easy to edit, version, and evolve — informed by real questions and edge cases surfaced during use.

3. Deliver it in context

Credible delivers that encoded meaning in context — to dashboards, products, APIs, and AI agents. At delivery time, context reflects the analytical intent, so answers align with how teams actually analyze data.
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Powered by Malloy, the model is readable by humans and machines, making analysis consistent and explainable.

What is Credible?

Credible is a context engine that brings shared meaning into the moments where data is analyzed and decisions are made.

Define meaning once.
Deliver it in context everywhere — across analytics, applications, and AI workflows.

Build and maintain shared meaning at the source

When shared meaning is encoded once, downstream teams stop reworking your logic.

Create shared meaning and model data with clear definitions, relationships, and transformations — using AI assistance where it helps, and full control where it matters. Work in your IDE, version models with Git, and promote changes safely with CI/CD.

Analyze with confidence — without chasing definitions

Everyone sees the same numbers — and understands what they represent.
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‍Spend less time validating numbers and more time answering questions. When shared context exists, teams spend less time explaining data and more time using it.

Turn Trusted Data into Powerful Experiences

When context is consistent, applications behave predictably.
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Use Credible’s APIs and MCP integrations to deliver context-rich data to applications and AI agents. The same shared meaning powers dashboards, products, and LLM-driven workflows.

Ready to put your data to work?

When the right context is available, analysis turns into action.

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Explore Modeler Experience

Why Credible?

Build Your Data Future on a Better Foundation

In the AI era, data systems don’t just need to store information — they need to deliver shared meaning in context. Credible is built as a durable foundation for doing exactly that, so teams can move fast without sacrificing clarity or control.

Future-Proof with an Open-Source Foundation

Credible is built on the open-source Malloy ecosystem — a complete set of tools for modeling data, serving it via APIs, and exploring it through workbooks and UIs.

This gives you true portability and no vendor lock-in. You can use the open stack directly, or layer on Credible’s context engine to add AI-powered workflows and enterprise scale — on your terms.

Scale with Confidence and Governance

Make shared meaning a production asset. Credible’s platform lets teams build and optimize semantic models from modular, reusable components and manage them with Git-based version control, automated testing, and CI/CD.

Fine-grained access controls, full auditability, and strong security make it safe to scale across teams, environments, and use cases — from analytics to applications to AI.

Let’s talk about your data’s future

Whether you’re exploring or ready to build, we’ll help you create a data foundation where shared meaning is always delivered in context.

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