Executive Summary

Enterprises are rapidly deploying AI agents to automate analytics and workflows, but data engineers, security, and compliance teams struggle to let those agents safely query centralized warehouses without exposing sensitive data or breaking governance. Today teams cobble together brittle connectors and manual policies, creating bottlenecks, audit gaps, and compliance risk. You could build a middle-layer SaaS platform that provides standardized, secure connectors to the dominant cloud DWHs (Snowflake, BigQuery, Redshift) with role-based access control, query sandboxing/rewriting, cost and rate limits, and end-to-end auditing and lineage tailored for agent-driven queries. Deliver this with a developer SDK and enterprise integrations so buyers can plug agents in quickly and target an average contract value around $30K per company. The addressable market is roughly $4.5B (150K enterprise buyers × $30K ACV), driven by AI agents moving from experimentation to production and consolidation around a few major DWHs that makes standard connectors feasible; market score 85/100 and revenue potential 82/100 suggest strong demand. You can stand out by shipping out-of-the-box compatibility with the three major warehouses, deep lineage and audit trails required for compliance, and tight IAM/MDM integrations to minimize deployment friction. The key challenges are integration complexity, earning trust from security teams, and competing with cloud-native controls—plan for pilots, compliance certifications, and channel partnerships to win enterprise deals.

Market Opportunity

Securely connect AI agents to data warehouses for safe querying targets a $4.5B = 150K companies × $30K ACV total addressable market with medium saturation and a year-over-year growth rate of 20% YoY — based on combined data & analytics platform growth and accelerated AI adoption (IDC/Forrester estimates).

Key trends driving demand: Adoption of AI agents is moving from experimentation to production, creating demand for governance and operational controls.; Consolidation around major cloud DWHs (Snowflake, BigQuery, Redshift) simplifies building standardized connectors.; Enterprises are prioritizing auditable data access and lineage, which increases willingness to pay for middle-layer controls.; Open-source agent frameworks lower prototyping costs but expose enterprises to security and governance gaps that commercial products can fill..

Key competitors include LangChain, ThoughtSpot, Interlynk (realistic startup).

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Securely connect AI agents to data warehouses for safe querying

Executive Summary

Market Validation

Market Opportunity

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