AI Safety Audit
Control behavior
Know what your agent really does, before your customers do.
Step 1
Your agent, connected through its API
An API connection is all it takes: Mankinds tests your agent as it actually runs, with its tools and its data.
What you gain
The system your users experience, evaluated as a whole.
- HTTP API, via cURL or OpenAPI import
- OpenAI
- Microsoft Copilot Studio
- Google Agent Runtime
Step 2
Your toughest users, before launch
Realistic conversations and tailored tests on what your requirements forbid.
What you gain
Gaps caught before your customers see them, and a clear signal to decide: ready, needs review or not ready.
- Multi-turn conversations
- Varied user profiles
- Tailored tests: injection, data extraction, bypassing your rules
Step 3
In production, checks on your traces
At regular intervals, Mankinds evaluates a sample of real conversations directly on your production traces, including the tools called and the documents retrieved.
What you gain
You know as soon as behavior changes: a regression triggers an alert.
- Traces: Langfuse, LangSmith, Datadog, OpenTelemetry, Amazon Bedrock AgentCore
- Alerts: email, Slack, Teams, webhook
Stable measurement, from one version to the next
The same scenarios are kept and replayed identically on every version, so comparisons hold. Anything a rule can check is checked deterministically, such as a data leak or a copied secret. An LLM judges only the qualitative part, one criterion at a time.
The questions we get asked
Which systems do you evaluate?
Any LLM-based system, in testing or in production: conversational assistants, RAG systems and tool-calling agents, reachable through an API.
Do you evaluate the model?
Mankinds evaluates your complete system, with its tools and its data.
Do you filter in real time?
Your guardrails filter in real time; Mankinds tests and samples, and proves they meet your requirements. The two work together.
How do we stop a release before deployment?
The tests plug into your CI pipeline: a failing release stops before production.