The Future of BI is
Agentic
Talk to your data, wherever it lives.
The AI Analytics Paradox
Why connecting AI to enterprise data has been a complex systems integration nightmare.
Locked in Silos
Valuable insights are locked away in disparate silos: S3, Snowflake, Postgres. Moving it all to one place is slow, expensive, and creates stale copies.
Language Barrier
AI models don't speak "Enterprise". Without business context, they fail to answer questions like "What was last quarter's churn?" accurately.
Latency Friction
Agentic flow requires conversational speed. Traditional pipelines and warehouse queries are too slow to maintain a fluid dialogue with your data.
The 5 Pillars of Agentic BI
A unified platform to bridge the gap between AI and Data.
Query Everything, Move Nothing
Connect directly to catalogs (AWS Glue, Unity, Snowflake) and storage (S3, Azure). Create a virtualized lakehouse and query data in place. No ETL required.
- Live Data Federation
- Zero Data Movement
Autonomous Performance
Apache Arrow engine + Reflections. Precomputed optimizations tailored for interactive query speed, completely transparent to the AI agent.
Unified Semantic Layer
Teach AI your business. Map raw tables to business logic. Powered by a built-in Polaris Catalog for Iceberg tables.
Agentic Interfaces
Built-in AI Agent for instant answers. Open Source MCP Server to securely connect external agents like ChatGPT to your data.
Native AI Functions
Embed intelligence in SQL. Use ai_classify and ai_generate to
analyze sentiment or extract data from PDFs directly in your queries.
Start the Conversation
The technical barriers are gone. What is the first question you will ask your data?
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