AI agents attempting to orchestrate multi-step tasks across backend systems are blocked by the absence of standardized, secure API coordination and permission frameworks that do not require UI intermediation. Current fragmentation across services means agents cannot reliably acquire, scope, delegate, or revoke permissions across heterogeneous systems at runtime. This prevents the agent-as-orchestrator model from functioning at scale and creates both security gaps and coordination failures.

AI agents orchestrating tasks across multiple APIs hit a wall because there's no standard way to request, scope, delegate, or revoke permissions across heterogeneous services at runtime — forcing humans back into the loop or creating dangerous security gaps.

Engineering teams at startups and mid-market companies building AI agents that need to chain actions across 3+ backend services (CRMs, payment systems, cloud infra, databases) without bespoke integration per service.

Teams are already spending weeks hand-rolling OAuth flows and permission logic per service per agent; enterprises won't deploy agentic workflows without auditable, least-privilege access controls — this is the compliance gate blocking seven-figure agent deployments today.

MVP is an open protocol spec plus a hosted broker service: agents request scoped, time-bound permission tokens via a unified API; service providers register adapters (starting with 5-10 high-value integrations like Stripe, AWS, Salesforce, GitHub); ship SDK for agent frameworks (LangChain, CrewAI) in week one.

The API management market is $6B+ and the agent orchestration layer sits at a new intersection of API gateways, IAM, and iPaaS — conservatively a $2B+ wedge as agentic workflows become default enterprise architecture.