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LLM Assurance for Agents and Production AI

Testing and monitoring for LLM agents, copilots and enterprise AI — hallucinations, jailbreaks, prompt injection and the failure modes that surface only in production.

The problem

An LLM demo rarely shows what breaks at scale: confident hallucinations, jailbreaks, prompt injection, inconsistent outputs, runaway cost and latency. LLM Assurance puts an agent through adversarial and operational testing so you ship with evidence, not hope.

What we validate

  • Hallucination testing
  • Jailbreak and prompt-injection testing
  • Agent failure and tool misuse
  • Output consistency and refusal behaviour
  • Unsafe outputs
  • Cost drift and latency
  • Evals and red-team scenarios
  • Monitoring design

What you receive

  • A Proof Score and verdict for the agent
  • A failure-mode catalogue with severity
  • Red-team findings
  • Monitoring and guardrail recommendations

Who it's for

Method, in brief

One principle: before trusting a system, we try to break it — in a controlled, documented way. We work across context, data, performance, calibration, robustness, bias, drift, fragility, overfitting and operational risk, then summarize a Proof Score and recommendations.

Pricing

Delivered as an LLM Assurance Audit (from €2,500). The fastest way to start is an LLM Assurance Snapshot.

Related: AI Model Assurance · Algorithm Assurance · Methodology · Pricing · Sample report · Contact

FAQ

Frequently asked questions

Do you test hallucinations?

Yes — we probe for confident but false or unsupported outputs and catalogue them by severity.

Do you test prompt injection and jailbreaks?

Yes — prompt injection, jailbreaks and unsafe-output paths are part of the audit.

Can you test agents and tool use?

Yes — agent failure, tool misuse, refusal behaviour, cost drift and latency are covered.

Do you provide monitoring recommendations?

Yes — we recommend guardrails, evals and monitoring to catch failures in production.