The AI Analytics Engine
Make your data Credible
Credible is the AI Analytics Engine. Write down what your data means once, and it delivers answers you can trust to every AI agent, data app, and dashboard that asks — fast, consistent, and secure.
How it works
From raw data to answers you can trust
The engine has one job: turn raw data into answers you can trust, for every person, agent, and app that asks. Credible collects the context behind your data from wherever it lives, writes it down once as a data model, and serves every question from that model – so every answer agrees, and every answer makes the next one better.
Collect your data's context
Your data arrives in whatever shape your systems produce it – tables, logs, spreadsheets, JSON. The context that gives it meaning is scattered: docs, decks, dashboards, old SQL, and the heads of a few experts.
Credible connects to wherever both live – over MCP, the open protocol that connects agents to tools – and captures the definitions, metrics, and relationships inside, so what your data means is in context before anything is written down.
Write it down once
A data model is the transform between two worlds: the events your systems record and the outcomes your business talks about. It compresses raw data into named concepts – revenue, active user, the rows the West team sees – each defined exactly once.
An agent drafts most of it with our open-source modeling skills; your team supplies the judgment the data can’t settle. You own the what. The engine owns the how – what to precompute, index, and materialize, in storage it brings along. No warehouse required.
One model, every answer
Every question – from a person, an agent over MCP, or your own app – enters through one gateway, is checked against the model’s access rules, and gets just the context it needs: the slice of the model that answers it, not the whole data model stuffed into every prompt.
The same answer, wherever the question is asked. And every question and answer leaves telemetry behind: the engine learns what gets asked and gets faster, cheaper, and more accurate on its own – the more you ask, the better it gets.
Get started
Your first data model
in minutes
Stop debating definitions. Start delivering answers.
Built on trust
Engineered like infrastructure
“AI-assisted reporting is at the front line of VideoAmp’s AI strategy, and Credible helps power it. The context engine is a cornerstone our AI roadmap is built on.”
Peter NummerdorSVP ProductVideoAmp“The ideas in Malloy are thirty years in the making, and today’s AI — with Malloy in its training data — writes it as fluently as Python. Semantic models improve AI accuracy dramatically.”
Lloyd TabbCo-founder of LookerMalloy, a Linux Foundation project“Credible helps us model our data once and ship it as scoped, governed MCP to internal users — no duplicated logic, no analyst bottleneck. It’s the best way to get trusted data into every Session, Agent, Skill and Plugin we develop.”
Raj LamgadayLead Data AnalystG2“Your platform is insane. Two report decks due the same day – I chatted with our model and had both before lunch. Reporting that took weeks is now a conversation we’re building into our product for our customers.”
Aquiles La GraveCo-founder & CPObars.com“We’re a lean team, and Credible is a force multiplier – AI answers grounded in definitions we control.”
Rory Armitage BurnsHead of Customer & DataHairburst“With Malloy we get a query language easier for LLMs and humans, and a semantic layer that captures our business definitions. I can’t recommend it enough for conversational analytics.”
Adam RibaudoData & Analytics LeadForm & Function“Semantic models are becoming the operating system for modern AI. Credible is building where the industry is headed — a place to build with AI agents that already understand your business.”
Miles GarveyFounderBrabble (ex-G2)“I’m the CTO supporting a national senior living healthcare organization. We are in the process of growing our internal data capabilities, and Credible gives me the leverage I need to tap into that capability now.”
Nick LindbergCTOHumanGood“This is what analytics engineering should have been all along – succinct models, versioned in git, ready for AI.”
Maksim AntipevSenior Analytics EngineerJust Eat Takeaway.com“I bring Credible into client engagements because it makes their data mean something from day one.”
Daliso ZuzeFounderZuze Consulting“Malloy gives our AI agents something SQL never could: the meaning behind the data. They answer with our definitions – auditable, access-controlled, correct.”
Chris WoodsonAI ArchitectAugment Risk“AI raises the bar for data modeling. Weak models become immediately visible when AI consumes them. Credible gives teams the tooling to build and evolve data models at AI speed, powered by Malloy.”
Joe ReisAuthor & AdvisorFundamentals of Data Engineering
“AI-assisted reporting is at the front line of VideoAmp’s AI strategy, and Credible helps power it. The context engine is a cornerstone our AI roadmap is built on.”
Peter NummerdorSVP ProductVideoAmp“The ideas in Malloy are thirty years in the making, and today’s AI — with Malloy in its training data — writes it as fluently as Python. Semantic models improve AI accuracy dramatically.”
Lloyd TabbCo-founder of LookerMalloy, a Linux Foundation project“Credible helps us model our data once and ship it as scoped, governed MCP to internal users — no duplicated logic, no analyst bottleneck. It’s the best way to get trusted data into every Session, Agent, Skill and Plugin we develop.”
Raj LamgadayLead Data AnalystG2“Your platform is insane. Two report decks due the same day – I chatted with our model and had both before lunch. Reporting that took weeks is now a conversation we’re building into our product for our customers.”
Aquiles La GraveCo-founder & CPObars.com“We’re a lean team, and Credible is a force multiplier – AI answers grounded in definitions we control.”
Rory Armitage BurnsHead of Customer & DataHairburst“With Malloy we get a query language easier for LLMs and humans, and a semantic layer that captures our business definitions. I can’t recommend it enough for conversational analytics.”
Adam RibaudoData & Analytics LeadForm & Function“Semantic models are becoming the operating system for modern AI. Credible is building where the industry is headed — a place to build with AI agents that already understand your business.”
Miles GarveyFounderBrabble (ex-G2)“I’m the CTO supporting a national senior living healthcare organization. We are in the process of growing our internal data capabilities, and Credible gives me the leverage I need to tap into that capability now.”
Nick LindbergCTOHumanGood“This is what analytics engineering should have been all along – succinct models, versioned in git, ready for AI.”
Maksim AntipevSenior Analytics EngineerJust Eat Takeaway.com“I bring Credible into client engagements because it makes their data mean something from day one.”
Daliso ZuzeFounderZuze Consulting“Malloy gives our AI agents something SQL never could: the meaning behind the data. They answer with our definitions – auditable, access-controlled, correct.”
Chris WoodsonAI ArchitectAugment Risk“AI raises the bar for data modeling. Weak models become immediately visible when AI consumes them. Credible gives teams the tooling to build and evolve data models at AI speed, powered by Malloy.”
Joe ReisAuthor & AdvisorFundamentals of Data Engineering
“AI-assisted reporting is at the front line of VideoAmp’s AI strategy, and Credible helps power it. The context engine is a cornerstone our AI roadmap is built on.”
Peter NummerdorSVP ProductVideoAmp“The ideas in Malloy are thirty years in the making, and today’s AI — with Malloy in its training data — writes it as fluently as Python. Semantic models improve AI accuracy dramatically.”
Lloyd TabbCo-founder of LookerMalloy, a Linux Foundation project“Credible helps us model our data once and ship it as scoped, governed MCP to internal users — no duplicated logic, no analyst bottleneck. It’s the best way to get trusted data into every Session, Agent, Skill and Plugin we develop.”
Raj LamgadayLead Data AnalystG2“Your platform is insane. Two report decks due the same day – I chatted with our model and had both before lunch. Reporting that took weeks is now a conversation we’re building into our product for our customers.”
Aquiles La GraveCo-founder & CPObars.com“We’re a lean team, and Credible is a force multiplier – AI answers grounded in definitions we control.”
Rory Armitage BurnsHead of Customer & DataHairburst“With Malloy we get a query language easier for LLMs and humans, and a semantic layer that captures our business definitions. I can’t recommend it enough for conversational analytics.”
Adam RibaudoData & Analytics LeadForm & Function“Semantic models are becoming the operating system for modern AI. Credible is building where the industry is headed — a place to build with AI agents that already understand your business.”
Miles GarveyFounderBrabble (ex-G2)“I’m the CTO supporting a national senior living healthcare organization. We are in the process of growing our internal data capabilities, and Credible gives me the leverage I need to tap into that capability now.”
Nick LindbergCTOHumanGood“This is what analytics engineering should have been all along – succinct models, versioned in git, ready for AI.”
Maksim AntipevSenior Analytics EngineerJust Eat Takeaway.com“I bring Credible into client engagements because it makes their data mean something from day one.”
Daliso ZuzeFounderZuze Consulting“Malloy gives our AI agents something SQL never could: the meaning behind the data. They answer with our definitions – auditable, access-controlled, correct.”
Chris WoodsonAI ArchitectAugment Risk“AI raises the bar for data modeling. Weak models become immediately visible when AI consumes them. Credible gives teams the tooling to build and evolve data models at AI speed, powered by Malloy.”
Joe ReisAuthor & AdvisorFundamentals of Data Engineering
Security
SOC 2 Type I audit in progress. Every query passes through one gateway, where it’s checked against the model’s access rules and logged to a permanent audit trail — and every customer’s data is fully isolated, by design.
Open source & ecosystem
Built on Malloy — created by the founders of Looker, production-hardened, and backed by a long-term commitment to backward compatibility.
Runs on AWS and Google Cloud. Connects to Snowflake, BigQuery, Databricks, Postgres, and more — or skip the warehouse and connect data where it already lives: transactional databases, spreadsheets, flat files.
Who it's for
One AI Analytics Engine — you tune to how each team works
Your AI is guessing. Credible makes it know.
Point an agent at raw data and it fills the gaps with unfounded confidence: invented joins, guessed definitions, stale data treated as current. Credible gives agents the model instead, over MCP — the open protocol that connects agents to tools. Each question gets just the slice of the model it needs, so the answer uses the right definitions, respects who can see what, and shows its work.
Answers you can trust — not hallucinations you have to debug.
Why Credible?
Built different: AI-first, enterprise-grade, open.
We didn't build an agent. You already own the harness.
Every vendor promises AI answers you can trust — inside their chat window, on their agent, in their app. That's a platform. Credible is the engine that plugs into the one you already use: Claude, ChatGPT, Gemini, and the agents you build yourself. One data model, the same answers, wherever the question gets asked.
Built for AI from day one
The market’s answers to AI analytics keep the modern data stack and upgrade one layer: a smarter workspace, or a faster warehouse. Credible took the layers out — one engine, built from scratch for a world where AI agents, not just people, consume your data. No wrappers, no workarounds, no legacy baggage.
Enterprise-grade by design
Fine-grained access controls, audit logging, and tenant isolation aren't add-ons — they're defined in the model, versioned in git, and enforced on every query. Built for production workloads, not demos.
Built on open source, not lock-in
Credible is built on Malloy — the open-source language the engine speaks, for writing down what data means. Your model is plain text in git: portable, inspectable, yours, and it runs on any warehouse without being locked into one. As active members of Apache Ossie, we're shaping the standard that keeps declared meaning portable across the data stack.
The AI Analytics Engine