Testing agents the way an attacker would.
Autonomous systems fail in ways traditional test suites were never designed to catch. We are building the platform that finds those failures before production does.
The problem
A passing test suite proves very little about an agent.
Conventional testing checks that known inputs produce expected outputs. An agent that can call tools, read untrusted content and decide its own next step has an input space nobody enumerated. The interesting failures are not in the paths you wrote tests for.
In a regulated business, that gap is not an engineering inconvenience. It is the reason the project does not get approval.
What it probes for
Prompt injection
Instructions smuggled through documents, tool output, or user content that redirect the agent away from its task.
Tool misuse
Correct tools called with wrong arguments, or called in sequences that were never anticipated when the boundaries were drawn.
Unsafe escalation
Actions taken that should have required a human — or handed to a human so often the system provides no value.
Silent drift
Behaviour that changes between model versions or prompt edits without any test failing to signal it.
How it runs
Inside your environment, in your pipeline.
- Runs on your infrastructure. No agent traffic, prompts or customer data leaves the network.
- Sits in CI as a gate, so a regression blocks a release rather than surfacing in an incident.
- Produces a report written for a risk committee, not just a developer.
Design partners
In private development with a small number of teams.
We are working with a handful of organisations shipping agents into regulated environments. Design partners get the platform at no cost during development, and a direct say in what it tests for.