Who This Is For

TrustLens is designed for machine learning practitioners who need to move beyond simple performance metrics to build truly reliable systems.

ML Engineers

Building mission-critical production systems where a high-confidence mistake has real-world consequences. Use TrustLens in your CI/CD pipeline to catch regressions in calibration or bias.

Data Scientists

When you need to justify model decisions to stakeholders or regulators. TrustLens provides the visual and quantitative evidence needed to explain model behavior.

Researchers

Benchmarking the reliability of new architectures. Go beyond the leaderboard accuracy and compare how different models represent classes or handle difficult edge cases.

AI Governance & Compliance Teams

Focused on safety, fairness, and regulatory compliance (like the EU AI Act). Subgroup performance and bias reports provide the transparency required for auditing.

---

Prerequisites

TrustLens is designed to be zero-friction. If you have a model with a .predict() and .predict_proba() method (like scikit-learn, XGBoost, LightGBM), you’re ready to go.