Most teams today test autonomous agents by reading the agent’s own account of what it did: a transcript, or a judge’s score over its final message. Agent Assurance grades the effect instead. Pointed at a codebase, it works out what the agent does, generates an end-to-end agent testing suite that spans agent functional testing, non-functional checks, and adversarial scenarios, invokes the agent for real, and judges every criterion against observed evidence: files that changed on disk, artifacts produced, and tool calls verified against the agent’s own declared tool surface. <\/p>\n Alongside pass and fail, Agent Assurance reports a third verdict, unable to verify, excluded from the pass rate and published as a number: the assurance gap. Every result in a report is one that was actually observed, and because the gap reflects how much an agent records about its own actions, teams can shrink it by making their agents more observable. <\/p>\n “Engineering teams are accumulating validation debt at exactly the layer where the stakes are highest. An agent’s account of what it did is the weakest evidence available about what it did – it is the one party with a reason to be wrong,” said Vipul Verma, Group SVP Of Engineering, TestMu AI. “Every tool in this space reports a pass rate. Agent Assurance reports the pass rate and the size of its own blind spot, because that is the only way the number becomes one you can trust to move.” <\/p>\n With Agent Assurance, teams can: <\/p>\n Test without writing tests \u2014 agent automation testing where the suite is derived from the codebase; the only input is how to invoke the agent, whether a command, an HTTP endpoint, an MCP server, or a workflow built on platforms like n8n. <\/p>\n Cover the adversarial surface by default \u2014 prompt injection, tool misuse, and instruction-override scenarios are generated as a first-class family, not an add-on. <\/p>\n Gate releases in CI \u2014 continuous agent testing in every pipeline, from agent smoke testing on each commit to full pre-release runs, with headless commands and exit codes that distinguish “the agent did something wrong” from “the harness could not test it.” <\/p>\n Track change with confidence \u2014 agent regression testing with run-over-run diffs that separate newly failing, newly fixed, and flaky results, since flakiness and regression call for opposite responses. <\/p>\n The Conversational Agent category is also expanding to the newest surface where software meets people: agents that appear on camera. With the platform’s new Video Agent Testing (Link<\/a>)\u00a0capability, a simulated human with a realistic face and voice joins a live video agent’s session, holds a genuine conversation, and grades the agent against team-defined success criteria, with every verdict traced to the exact moment in the recording that earned it. Anything unverifiable from the recording is deliberately counted as not met, a strict standard for a category where the recording is the evidence: a video agent never earns credit for a moment the evaluator could not observe. <\/p>\n The Conversational Agent category is generally available on the TestMu AI platform today. The Autonomous Agent category is available in early access and runs from the terminal as rook, with models executing in the TestMu AI controller so no provider API keys are needed locally. To get started, visit\u00a0Link<\/a>. <\/p>\n About TestMu AI <\/p>\n TestMu AI<\/a>\u00a0is the world’s first Agentic AI-native Quality Engineering platform, designed to enable organizations to automate and scale testing with intelligence at its core. By combining autonomous capabilities with seamless integration across modern development workflows, TestMu AI empowers teams to deliver faster, more reliable, and secure software in an AI-first world. <\/p>\n For more information, visit\u00a0TestMu AI<\/a> <\/p>\n View original content to download multimedia:https:\/\/www.prnewswire.com\/news-releases\/testmu-ai-launches-agent-assurance-to-verify-ai-agents-before-they-ship-302854190.html<\/a> <\/p>\n<\/a> TestMu AI (Formerly LambdaTest) <\/p>\n
<\/a> Cision <\/p>\n