Executive Summary

Enterprises and platform teams increasingly run collections of specialized AI agents—task-specific bots, retrieval agents, and orchestration workflows—that must coordinate across models, data sources, and vendor APIs, creating brittle point-to-point integrations and opaque access to systems. This problem is acute for mid-market and enterprise buyers (roughly 500,000 accounts) who require audit trails, policy enforcement, and predictable latency when agents act on sensitive resources. The product is an agent interoperability layer: a vendor-neutral protocol and secure runtime that exposes discovery, messaging, shared state, policy enforcement, and connectors, plus SDKs for popular agent frameworks to reduce integration friction. The market is compelling now—estimated TAM of $15.0B (500K buyers × $30K ACV), supported by a 90/100 market score and an 86/100 revenue potential—because teams are both proliferating agents and adopting heterogeneous model stacks while procurement and regulators demand governance and auditability. You can stand out by delivering a lightweight open protocol plus an enterprise-grade runtime with built-in audit logs, fine-grained access control, and certified connectors to major clouds and data systems, combined with go-to-market via SI partners and framework integrations. The challenges are real: winning standards adoption and network effects against a medium-competition landscape, proving security/compliance at scale, and executing long enterprise sales cycles; these are surmountable with clear ROI metrics, partner-led deployment, and an initial focus on high-value verticals.

Market Opportunity

Agent interoperability layer — unified protocol and runtime for AI agents targets a $15.0B = 500K mid-market & enterprise buyers × $30K ACV (integration, orchestration, and AI infra spend) total addressable market with medium saturation and a year-over-year growth rate of 25% YoY — aggregated forecast from iPaaS and AI infrastructure market reports (Gartner/IDC commentary on AI infra and integration growth).

Key trends driving demand: Proliferation of agent frameworks — more teams are deploying specialized agents, which increases demand for cross-agent coordination.; Enterprise demand for governance — regulators and procurement teams require audit trails and policy enforcement when AI accesses systems.; Shift to heterogeneous AI stacks — companies choose best-of-breed models and providers, creating need for vendor-neutral orchestration..

Key competitors include LangChain, Microsoft Power Platform / Copilot + Power Automate, Zapier / Make (Integromat).

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Agent interoperability layer — unified protocol and runtime for AI agents

Executive Summary

Market Validation

Market Opportunity

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