When multi-agent stacks take autonomous actions with real-world consequences, existing observability and audit systems cannot produce provable chain-of-custody for agent intent and execution across requester, approver, transformer, and executor roles. Legal and compliance scrutiny in high-stakes deployments requires traceable accountability that current frameworks cannot provide. This is a blocking gap for enterprise adoption of agentic systems in regulated industries.

When a multi-agent workflow causes a costly error or compliance violation, no one can trace which agent decided what, making enterprises legally unable to deploy agentic systems in regulated contexts.

Engineering and compliance leads at enterprises deploying multi-agent systems in regulated industries (fintech, healthcare, legal, defense).

Regulated enterprises are actively blocked from scaling agentic deployments because they cannot satisfy audit and liability requirements — they'd pay for infrastructure that unblocks millions in automation value, similar to how they already pay for SOC2/audit tooling.

MVP is an open-source SDK that instruments agent-to-agent calls with cryptographically signed intent/action envelopes (requester→approver→transformer→executor), plus a hosted dashboard for chain-of-custody replay and blame attribution — start with LangGraph and CrewAI integrations.

Subset of the $15B+ observability market intersected with the rapidly growing enterprise AI agent market; comparable to early compliance-as-a-service plays like Vanta ($1B+ valuations).