AI Data Analyst

Everything you need to make AI interact with enterprise data accurately, securely, and at scale

Natural Language to Trusted SQL - Transforms plain business questions from users or AI agents into optimized SQL using verified semantic reasoning about enterprise metrics, relationships, and definitions

Autonomous Context Discovery - Continuously crawls data warehouses, catalogs, Confluence documents, chat history, and user feedback to build and maintain a living enterprise semantic graph

Self Healing Semantic Model - Automatically detects conflicting metric definitions, semantic drift, and duplicate entities, proposing and applying corrections to maintain data accuracy over time

AI Native Query Execution - Participates directly in query planning so AI-generated SQL is grounded in verified business definitions, eliminating hallucinated column references and join errors

Governed Cross Platform Execution - Executes queries across warehouses, databases, and lakehouses while enforcing row-level, column-level, and role-based access policies in real time

MCP & Agent API Access - Exposes the semantic layer via MCP and REST APIs enabling AI coding agents and enterprise copilots to query data without hallucinating structure or relationships