Agent tool discovery and self-verification framework for autonomous tasks

Executive Summary

Enterprises and engineering teams deploying autonomous agents face a growing pain: multi-step tool orchestration driven by generative models often produces unpredictable or incorrect actions that create business risk, debugging burden, and compliance gaps. This is a broad problem—targeting roughly 2 million potential business buyers—who increasingly demand auditability and deterministic checks for automated actions. You could build a developer-first framework that discovers available tools, instruments agent workflows, and runs self-verification checks and deterministic tests at runtime, producing human-readable failure explanations and immutable audit trails. Offer a verification DSL, CI/CD integrations, SDKs, and connectors so teams can enforce policies, reproduce decisions, and automate rollback or remediation. This is a timely market opportunity: an estimated $6.0B addressable market (2M businesses × $3K ACV), high market and revenue scores, and strong demand as enterprises prioritize governance for AI-driven workflows. Where this could stand out is by combining automated tool discovery with verifiable runtime checks and excellent developer ergonomics—while being upfront about challenges like integration complexity and the difficulty of proving absolute correctness, and focusing initial go-to-market on compliance-heavy verticals to build trust.