Governance gap blocks adaptive process orchestration — policy-as-code control plane

Many mid-to-large enterprises — roughly 50,000 organizations in the addressable set — struggle to enforce consistent governance across a growing set of heterogeneous orchestration engines (Kubernetes workflows, Airflow, Camunda, RPA, etc.), leaving security and compliance teams with fragmented policies, weak execution-level visibility, and costly manual remediation. The problem is acute in regulated industries where auditability and change-control slow innovation and increase operational risk. You could build a policy-as-code control plane: a centralized, engine-agnostic layer that provides policy authoring, testing, enforcement hooks, and an execution-observability plane that mines logs and suggests policies using ML, delivered as an enterprise SaaS with an ACV target near $600K. This product maps directly to a $30B market (50,000 customers × $600K ACV), and market signals are strong — cloud-native orchestration adoption, investment in process observability/mining, and maturing AI-assisted automation together justify enterprise appetite now. To stand out, focus on rigorous, provable policy semantics, deep execution-level observability, and AI-assisted but explainable policy inference plus turnkey integrations into existing GRC stacks so you can demonstrate reduced audit time and fewer manual interventions. Expect medium competition from incumbent GRC vendors and cloud providers, long sales cycles, and the technical challenge of building trustworthy AI and low-friction integrations; those are solvable but require disciplined product engineering and early enterprise reference customers.