Enable local AI assistants to read DB schemas and execute/interpret SQL results

Enable local AI assistants to read DB schemas and execute/interpret SQL results targets a $3.6B = 120,000 developer teams × $30K ACV (annual tooling + integrations budget) total addressable market with medium saturation and a year-over-year growth rate of ~20% YoY — estimated growth of AI developer tools and internal AI assistant markets (industry reports, 2023-2025 trend data).

Key trends driving demand: Self-hosted and on-prem AI demand is rising as organizations prioritize data residency and compliance — this creates a need for secure local connectors.; LLMs are increasingly used as developer assistants and analytics copilots — teams demand tight DB integrations that understand schema and types.; Open-source LLMs and local inference lower barriers to running AI on private data — enabling lower-latency, cheaper, and offline-capable assistant experiences.; Platform ecosystems (Supabase, Postgres) are expanding extensibility and encourage third-party plugins, creating distribution channels for specialized connectors..