TrustQE is a purpose-built testing platform for AI systems — covering RAG pipelines, LLM outputs, agent behaviour, security vulnerabilities, and the Responsible AI checks that regulators and boards now expect.
No signup needed to try it. Full platform trial access is coming soon.
Checks whether your AI's answers are actually backed by what it retrieved, not made up.
Scores your AI's answers against your own test cases, not a generic third-party benchmark.
Probes your AI for prompt injection, jailbreaks, and data leaks before attackers do.
Checks whether your AI agent completes multi-step tasks correctly and recovers when something goes wrong.
Tests your AI for bias, unsafe responses, and the other issues regulators and boards care about.
Tracks your AI's quality over time so you catch regressions before your users do.
Explains why your AI reached a given answer, for audit and governance needs.
Point TrustQE at a running endpoint. Connect your RAG pipeline, LLM, or agent directly, and every module tests real, live responses.
Nothing has to leave your network. Paste in responses you've already collected — most modules score them with the same depth as a live run. A few real-time checks, like drift monitoring, still need a live connection.
No CLI access or scripting knowledge required. Explore results, review module outputs, and build evidence packs for stakeholders and auditors.
Fits naturally into automation and pipeline workflows. Run any module from the terminal, script multi-module test sequences, pipe results into your own tooling.

System health at a glance — with open gate failures surfaced immediately, not buried in a report.

Test results mapped directly to EU AI Act, ISO 42001, and NIST AI RMF controls — backed by a tamper-evident, HMAC-signed audit trail for security and procurement review.

Every test pack — faithfulness, hallucination, injection, fairness, drift — with a clear pass, warn, or block decision against your own quality gates.

Compare quality gates across providers or endpoints side by side — vendor-neutral, so the data drives the decision.
Screens shown from the TrustQE workbench with representative sample data.
TrustQE ingests results from popular evaluation frameworks and observability platforms, and plugs into the agent frameworks and CI/CD pipelines your team already runs — so it fits where your team already works.
An AI system isn't production-ready because it works in a demo. It's production-ready when it can be tested, explained, and defended.
Most AI testing today is ad hoc — prompt experiments, manual spot-checks, borrowed benchmark scores. TrustQE replaces that with structured, repeatable assurance that stands up to audit.
Trial access to connect the platform to your own AI system directly is coming soon. Prefer to talk it through first? Get in touch directly.