TestMachine

What can a better observability layer for your AI agents do for your workflow?

TestMachine lets you enforce policy and guidance on your agents and finds new policies to cover risks you didn't anticipate.

See what TestMachine can do for you today.
testmachine.ai/blog/introduci…

We’re excited for everyone to try out TestMachine, a trust and observability layer for AI agents. TestMachine records connected tool calls, checks them against the rules your team writes, and blocks calls that break them before execution.

What makes us different from other tools?
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Check out our blog:
testmachine.ai/blog/introduci…

We're excited to announce the launch of TestMachine. An MCP gateway layer that gives you powerful observability and monitoring of your AI agents.

Does your team have many agents without much visibility between people? TestMachine's observability layer allows your team to maximize collaboration and adoption of AI agents.

TestMachine observes agent activity and, with our state of the art data factory, can create complex situations to test how your agents react, so we can build policies with you to protect you against unauthorized actions.

Check out our blog and try it out for yourself today!
testmachine.ai/blog/introduci…

288 AI incidents were reported between January 1 and October 22 this year.

In February, an AI coding agent deleted a course platform's production database, along with its backups.

The agent had permission to do it. Nobody had written the rule that should have applied.

Teams are giving agents real work before they know which rules those agents need.

So we built TestMachine to help teams build and enforce those policies. It shows your team what your agents actually do. You write rules in plain English, and TestMachine checks each connected action against them before it runs, allowing or blocking it.

testmachine.ai/blog/introduci…

Lots of companies are adopting AI agents into their everyday workflow without knowing all the risks. You could set policies and still be exposed to unauthorized actions you never thought of.

For instance, prompt injection is a major attack that agents are susceptible to. Say an agent reads and replies to your emails. An attacker can hide instructions in a message, and the agent may follow them without you noticing.

This is just one way agents can take actions you never expected. Your guardrails and policies may not be enough.

Do you think you are prepared and covered against all forms of AI agent risks?