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Credible transforms your raw data into a governed semantic layer through an AI-powered workflow that understands your data’s context and business meaning. Our platform combines intelligent data analysis with a streamlined development experience in VS Code.

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How AI-Powered Modeling Works

When you connect your data sources, Credible begins comprehensive indexing of your entire data environment:
  • Database schemas: Tables, columns, data types, and relationships
  • SQL query logs: Historical queries reveal common joins, filters, and business logic patterns
  • Data catalogs: Existing documentation and metadata about your data
  • Data warehouse artifacts: Views, stored procedures, and existing transformations
  • Unstructured context: Business documentation that provides semantic understanding
This indexing process identifies key entities—dimensions, measures, join relationships—giving our AI the context it needs to provide intelligent, trustworthy suggestions rather than generic guesses.

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The Modeling Workflow

1. Connect Your Data

Link data sources so you can build and query semantic models of your dataConnect your databases to Credible. The platform immediately begins indexing schemas, query patterns, and metadata to power intelligent AI assistance.

2. Build Your Model

Develop in VS Code with AI assistanceSet up the VS Code extension, connect to your indexed data, and build semantic models with intelligent AI suggestions tailored to your data patterns.

3. Publish Your Models

Make models available across your organizationVersion and publish your semantic models using Git workflows. Enable teams to discover and use your models consistently.

Optional: Build Governed Notebooks

Create data stories and documentationBuild Malloy notebooks to demonstrate analysis patterns, document standard workflows, and create simple dashboards that showcase your model’s capabilities.
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