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Executive Summary

Many enterprises embedding large language models into products and internal workflows now face uncontrolled model calls, inadvertent data exfiltration, inconsistent safety transformations, and a growing need for auditable controls—issues that fall squarely on security, legal, and compliance teams at roughly 200,000 addressable enterprises. The problem is acute in regulated industries (finance, healthcare, government) where a single misrouted prompt can create legal exposure, and current point solutions (prompt engineering, app-level guards) are fragmented and non-versionable. You could build a centralized AI policy gateway that intercepts model requests and responses in real time to rewrite, redact, block, or annotate content according to versionable policy-as-code; provide policy testing and CI integration, end-to-end audit trails, model adapters for major API providers and on-prem runtimes, and connectors to SIEM, DLP, and identity systems. The product would aim for sub-50ms median added latency, deterministic policy evaluation, and per-tenant policy layers so customers can audit and roll back changes with cryptographic evidence. This market is attractive now because enterprise LLM adoption is accelerating and regulators (for example, the EU AI Act and sector-specific guidance) are increasing demand for auditable, centralized controls; the addressable spend is credible—approximately $30.0B if 200,000 enterprises spend $150K ACV on AI governance/security. With a market score of 92/100 and revenue potential at 90/100, buyers have both the financial capacity and regulatory incentive to procure such tooling in the next 12–24 months. You can stand out by focusing on model-agnostic, runtime policy enforcement with strong developer ergonomics (policy-as-code, CI hooks), cryptographically verifiable audit logs, and partnerships with cloud and security vendors to reduce integration friction. Key challenges to acknowledge are the technical work to keep latency and false positives low, the operational burden of many customer-specific integrations, and the need to build trust with infosec teams—these are solvable but require disciplined product and go-to-market execution rather than optimistic assumptions.

Executive Summary

Centralized AI policy gateway — rewrite, block, redact, and audit model calls

Executive Summary

Centralized AI policy gateway — rewrite, block, redact, and audit model calls

Executive Summary

Market Validation

Market Opportunity

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Ongoing security costs — prioritize & automate continuous remediation

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