Executive Summary

Many companies that want to deploy multi-step AI agents lack a safe, auditable way to let those agents query live cloud data warehouses; data engineers, security/GRC teams and ML/automation owners currently stitch together brittle SQL proxies, overly permissive credentials, or expose sensitive tables, creating risk, cost blowouts and compliance gaps. This pain is concentrated in the ~250,000 businesses running cloud DWHs who face both operational and auditability burdens when agents need live data. You could build a vendor-neutral middleware that sits between agents and Snowflake/BigQuery/Redshift, offering schema-aware adapters, fine-grained RBAC, per-agent cost budgets, query rewriting/sandboxing, and immutable audit logs with lineage and explainability APIs. Delivered as managed control plane + lightweight connector, it would include a policy UI, SDKs for popular agent frameworks, and enterprise-ready telemetry for billing and monitoring. The market looks attractive right now: a $7.5B addressable market (250K customers × $30K ACV), an 88/100 market score and 86/100 revenue potential driven by agentization of workflows, DWH standardization, and rising enterprise demand for AI governance. Competition is medium, but widespread standardization of DWHs lowers integration cost and accelerates customer adoption. You can differentiate by making auditability and deterministic policy enforcement first-class—immutable logs, cryptographic verification of queries, and per-agent cost control combined with out-of-the-box connectors for the big three DWHs. Real challenges are integration with diverse security stacks, proving low-latency reliability at scale, and winning initial enterprise pilots and compliance certifications, so plan for targeted pilots and SOC/ISO credentials early.

Market Opportunity

Safe, auditable middleware to let AI agents query your data warehouse targets a $7.5B = 250K businesses with cloud data warehouses × $30K ACV total addressable market with medium saturation and a year-over-year growth rate of 14% YoY — Growth estimate based on combined cloud data warehouse and data-infrastructure market expansion (sources: Gartner, MarketsandMarkets estimates for data & analytics and DWH adoption).

Key trends driving demand: Agentization of workflows — companies are moving from single-query LLM prompts to multi-step agents that require live data access, which creates demand for safe data access layers.; Cloud DWH ubiquity and standardization — with Snowflake, BigQuery and Redshift dominance, standardized connectors and query patterns make middleware integration feasible and attractive.; Enterprise focus on AI governance — teams need audit logs, RBAC, and cost controls as AI touches more production workflows, increasing demand for control planes.; Shift from experiment to production — organizations that piloted LLMs in 2023–2024 now need operational products to move agents into production safely..

Key competitors include LangChain, LlamaIndex (GPT Index), Hex.

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Safe, auditable middleware to let AI agents query your data warehouse

Executive Summary

Market Validation

Market Opportunity

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