AI layer

An accurate AI layer on your data

Datalyze gets your data ready for AI. We bring it into one warehouse, model it into clean tables, and add a semantic layer with the business context an AI needs. You ask questions in plain English and get answers you can trust.

150+Companies trust Datalyze
1source of truth
4-6 weeksto an AI layer
  • CRED logo, a Datalyze analytics client
  • AWeber logo, a Datalyze analytics client
  • Silverfort logo, a Datalyze analytics client
  • Final Round AI logo, a Datalyze analytics client
  • Pixis logo, a Datalyze analytics client
  • Coursebox logo, a Datalyze analytics client
  • Uplers logo, a Datalyze analytics client
  • Delightree logo, a Datalyze analytics client
  • AlgoTest logo, a Datalyze analytics client
  • Magma logo, a Datalyze analytics client
  • TermPlus logo, a Datalyze analytics client
  • Kryptos logo, a Datalyze analytics client
  • Superhote logo, a Datalyze analytics client
  • Wellness Coach logo, a Datalyze analytics client
  • Inferless logo, a Datalyze analytics client
  • Skip logo, a Datalyze analytics client
  • Copyfy logo, a Datalyze analytics client
  • Foriio logo, a Datalyze analytics client
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  • Sarvam AI logo, a Datalyze analytics client
  • Kruzee logo, a Datalyze analytics client
  • TrueFoundry logo, a Datalyze analytics client
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AI layer connected to web, Meta Ads, Google Ads and CRM data, summarizing growth and performance in plain language
  1. 01Warehouse

    Get all of your data into one place

    Product analytics, billing, CRM, ads and your own database, loaded into one data warehouse like BigQuery or Snowflake.

  2. 02Modelling

    Model the data into clean marts

    Raw tables turned into clean, tested marts: users, accounts, orders, sessions, revenue. Each one is built to answer real questions, with one definition for every metric.

  3. 03Semantic layer

    Add a semantic layer with business context

    What each table and column means, how tables join, how every metric is calculated, and example queries for common questions. This is what stops the AI from guessing.

  4. 04Connect

    Connect it to your AI tool, or call it over MCP

    Connect the GitHub repo to an AI analytics tool, or expose the layer over MCP so Claude, ChatGPT or your own AI tool can query it directly.

You get an AI your whole team can ask questions in plain English, and answers that you can trust.

Final step

Get answers from AI
you can trust

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