The AI Analytics Engine
Make your data Credible
Analyze data, build data apps, deploy AI agents on a governed foundation — fast, efficient, and secure. No warehouse, no pipelines, no data team required.
How it works
From the data you have to answers you can trust
Connect your data, describe your domain, and ask for what you want. The engine generates everything else, and every person, agent, and app gets its answers from the same model, so every answer agrees.
Connect the data you already have
Postgres, MySQL, spreadsheets, CSVs – or a warehouse, if you have one. Credentials stay with Credible, never on a laptop.
Credible helps you collect what the data means from wherever that lives – old docs, dashboards, SQL, the heads of a few experts – before a line of the data model is written.
Describe your domain
What counts as revenue, what a customer is, which window is “last month”, who sees what. An agent drafts the data model from your answers with our open-source modeling skills; you confirm what’s right.
You own the what. The engine generates the how – the apps, the AI agents, and everything else.
Ask questions. Build on the answers.
Ask your data a question, build an app on it, or give the agent you’re building the same model over MCP. Every question goes through one gateway, is checked against who’s allowed to see what, and is answered from the same definitions.
The same answer, wherever it’s asked – and every question makes the engine faster and more accurate for the next one.
Get started
Connect your data.
Ask a question. Five minutes.
Free to start. No seats, no sales call, no warehouse to set up first.
Built on trust
Fast, efficient, and secure
“We’re a lean team, and Credible is a force multiplier – AI answers grounded in definitions we control.”
Rory Armitage BurnsHead of Customer & DataHairburst“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“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“I bring Credible into client engagements because it makes their data mean something from day one.”
Daliso ZuzeFounderZuze Consulting“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)“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-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“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“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“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“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“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
“We’re a lean team, and Credible is a force multiplier – AI answers grounded in definitions we control.”
Rory Armitage BurnsHead of Customer & DataHairburst“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“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“I bring Credible into client engagements because it makes their data mean something from day one.”
Daliso ZuzeFounderZuze Consulting“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)“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-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“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“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“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“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“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
“We’re a lean team, and Credible is a force multiplier – AI answers grounded in definitions we control.”
Rory Armitage BurnsHead of Customer & DataHairburst“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“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“I bring Credible into client engagements because it makes their data mean something from day one.”
Daliso ZuzeFounderZuze Consulting“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)“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-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“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“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“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“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“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 compliant. Every query passes through one gateway that checks who’s allowed to see what and logs it to a permanent audit trail. Every customer’s data is 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
Not just for the data team
Data tools have always been built for a central data team, bought by one, and handed to everyone else as a dashboard. Most companies don't have a data team, and the ones that do can't keep up with the questions. Credible is for the person who owns the numbers, the engineer shipping an agent, and the data team that's done being the bottleneck.
Build agents and apps in minutes. Ship them safely.
An agent can build a working app in minutes. Running it safely in production is the hard part. Credible gives your agent the right context over MCP and enforces access control on every query, so it answers fast, correctly, and securely from day one.
Context you can trust — not hallucinations you have to debug.
Answers, apps, and agents, with the team you already have.
You have a Postgres database, a few spreadsheets, a folder of exports, and nobody whose job is data. Connect them, describe your domain, and your agent drafts the data model. Then ask it questions, build apps on it, and give your agents the same model. The engine generates everything else and keeps it all fast and consistent.
Like having a data engineer on staff.
Be the foundation, not the bottleneck.
You own what the data means; everyone else builds on it. Apps, agents, and every question run on one data model, and the model is code: Malloy, succinct enough to read, expressive enough to hold definitions, relationships, and who sees what. The engine generates the pipelines, storage, and serving. You review the diffs, versioned in git, tested in CI.
Your IDE. Your workflow. AI that actually helps.
Why Credible?
Built for the team you have, and the agent you already use.
We didn't build an agent. Credible is the engine behind Claude, ChatGPT, Gemini, Cursor, and the agents you build yourself. Describe your domain, and it generates everything else — the apps, the pipelines, the storage — and answers every agent, app, and person from the same data model, with access control on every query.
Built for the team you have
No warehouse to stand up, no pipelines to run, nothing to babysit. And the engine is growing to cover the whole job: getting data in, trying changes safely, and letting agents work without touching production.
Works with the agent you already use
Claude, ChatGPT, Gemini, Cursor, and the agents you build yourself, over MCP. One connection per agent, the same model behind all of them, and nothing to rebuild when you switch. Production-ready, not a demo.
Yours to keep
Built on Malloy, the open-source language for what your data means. Your data model is plain files, and through Apache Ossie, that meaning is becoming an open standard. Stop paying tomorrow and you'd still have it.