Executive Summary

Enterprises adopting multiple vendor-specific AI agents are now running into a practical fragmentation problem: roughly 90,000 relevant organizations are investing in agent capabilities but face costly point-to-point integrations, duplicated connectors, inconsistent state and tool semantics, and limited observability and policy control across agents. This creates brittle multi-agent workflows where handoffs, planning and governance are manual or ad hoc, driving integration and security overhead for engineering and security teams. You could build a neutral protocol plus a production-grade runtime that provides capability discovery, a canonical message/state model, secure tool invocation, policy enforcement hooks, and end-to-end observability, delivered as an open specification plus an enterprise runtime, SDKs and starter adapters for top vendors and initial verticals such as financial services and healthcare. The product would combine an open standard to encourage ecosystem adoption with a commercial, hardened runtime that enterprises license for compliance, SLA, and support needs. The timing is favorable: proliferation of vendor agents and a shift toward multi-agent workflows are creating demand now, and the arithmetic is clear — 90,000 target enterprises × $200K average annual spend on integration, orchestration and governance implies an $18.0B addressable market; market score 92/100 and revenue potential 88/100 reflect strong opportunity with medium competition. To stand out you must be governance-first and vendor-neutral, prioritize developer ergonomics and fast adapter paths, and secure enterprise certifications (e.g., SOC 2, ISO) so CIOs and CISOs will buy; strengths include clear enterprise willingness to pay and an early window to shape standards, while challenges include overcoming network effects, potential resistance from closed-platform vendors, and the complexity of running a standards process plus an enterprise-grade commercial product.

Executive Summary

Market Opportunity

Standard protocol and runtime to connect heterogeneous AI agents targets a $18.0B = 90,000 relevant enterprises × $200K ACV (AI integration + orchestration + governance spend per org per year) total addressable market with medium saturation and a year-over-year growth rate of 30% YoY — based on IDC/Forrester estimates for AI infrastructure and orchestration spending in enterprise IT (2024-2026 forecasts).

Key trends driving demand: Proliferation of vendor-specific agents — enterprises are adopting multiple agents from different vendors, creating demand for a neutral interoperability layer.; Shift from single-agent apps to multi-agent workflows — businesses want agents to collaborate (planning, tool-use, handoffs), which requires standardized protocols and shared state.; Rising compliance and security requirements — CISOs demand observability and policy enforcement for autonomous agent actions, opening opportunities for governance tooling.; Composability and marketplaces — teams want to mix and match best-of-breed agents, which creates demand for registries and connector marketplaces to discover and monetize agent capabilities..

Key competitors include LangChain, Hugging Face, Zapier.

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Standard protocol and runtime to connect heterogeneous AI agents

Executive Summary

Standard protocol and runtime to connect heterogeneous AI agents

Executive Summary

Market Validation

Market Opportunity

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