Executive Summary

Companies deploying production AI agents—development teams, security and compliance officers, and executives—are exposed to agents taking unintended destructive actions (data loss, misconfigured infrastructure, unauthorized transactions and regulatory violations). Current controls (static testing, manual review, and post-incident forensics) fail to stop harmful runtime behavior, leaving organizations vulnerable to outages, fines, and reputational damage. You could build a runtime governance platform that sits between agents and their execution targets to provide low-latency, policy-as-code enforcement, pre-execution simulation/sandboxing, developer SDKs, and immutable audit trails that block or roll back forbidden actions. Instrumenting diverse agent frameworks and keeping latency acceptable are nontrivial engineering challenges, but an SDK-first, cloud-native integration strategy would lower adoption friction for dev teams. The market is timely and large: agentization, increasing regulatory scrutiny, and the shift-left security trend are driving urgency across ~140,000 target companies, which at a $60K average contract value equates to an $8.4B addressable market. Buyers will pay for proven incident prevention and auditable evidence to satisfy regulators and reduce exposure. To stand out, prioritize developer ergonomics (policy-as-code SDKs), guaranteed runtime enforcement with measurable SLAs, and rich auditability for compliance; these capabilities plus a clear ROI case (reduced incident costs versus a ~$60K ACV) can overcome medium competition, but expect a long enterprise sales cycle and significant integration work.

Market Opportunity

Prevent production AI agents from executing unintended destructive actions targets a $8.4B = 140K target companies × $60K ACV total addressable market with medium saturation and a year-over-year growth rate of 30% YoY (estimated growth for AI security and governance market based on Gartner & McKinsey reports on enterprise AI adoption, 2023-2025).

Key trends driving demand: Agentization — companies are moving from chatbots to agents that execute actions, creating demand for runtime governance and execution controls.; Regulatory focus — governments and industries are increasing scrutiny on AI decision-making and auditability, raising procurement urgency.; Shift-left security — developers expect policy-as-code and developer-friendly SDKs that integrate governance early in the delivery pipeline.; Observability + ML — combining telemetry from agent actions with ML anomaly detection enables automated detection of rogue behaviors at scale..

Key competitors include OpenAI (safety & tools), LangChain, Open Policy Agent (OPA).

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Prevent production AI agents from executing unintended destructive actions

Executive Summary

Market Validation

Market Opportunity

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