Is the Data Layer for Agent Consumption Just Text-to-SQL?

Agents don't think in filters - they think in meaning.
They combine world knowledge with user context to craft semantic queries based on intent, not keywords.

The problem: The industry is stuck translating natural language into pre-set SQL filters. Rigid schemas. Static filters.

Our agent-native data layer: Vector embeddings + semantic matching for company activities:

• What functions are they building?

• What migrations are happening?

• Who's joining and leaving? Static filters for deterministic data:

• Headcount, location, funding stage The bet: Agents are smart enough to query both static and semantic fields. We're building for Agents that reason around meaning.