Autonomous agent deployments in finance, healthcare, and other regulated sectors lack runtime hardening, compliance auditing, and trust attestation infrastructure necessary for enterprise adoption. Capital investment in agent capabilities is outpacing the development of governance layers, creating a widening gap that is the primary barrier to regulated-industry deployment. No marketplace or coordination layer currently exists to certify, monitor, or remediate agent behavior against regulatory standards at scale.

Enterprises in regulated industries cannot deploy autonomous agents because no runtime governance layer exists to certify, audit, and attest agent behavior against regulatory standards — blocking billions in potential deployments.

Enterprise AI/ML platform leads at mid-to-large financial services, healthcare, and insurance firms who have agent prototypes stuck in sandbox due to compliance sign-off gaps.

Regulated enterprises already spend $15-50K+ per model on manual AI risk assessments and GRC tooling; a real-time, agent-native compliance layer collapses weeks of audit work into continuous attestation, and compliance teams will mandate it as a procurement requirement.

MVP: an agent sidecar/proxy that intercepts agent actions at runtime, evaluates them against pluggable policy modules (SOC2, HIPAA, SEC/FINRA rulesets), and emits signed audit logs with trust attestations — start with one vertical (fintech agent guardrails) and a policy marketplace where compliance consultants and firms publish certified rule packs.

AI governance/GRC market projected at $5B+ by 2028; regulated-industry agent deployments alone represent a $2B+ infrastructure spend as autonomous agents move from sandbox to production.