The Scalable Testing Engine

PiCrystal

PiCrystal is a highly efficient, automated, extensible and model agnostic testing solution, which generates and executes a metrics suite to evaluate the behavior of any black-box model on certain data

PiCrystal

What can you do with PiCrystal?

PiCrystal is the core of our AI Trust Platform and enables data scientists and ML engineers to automate validation tests on any AI/ML system — making its behavior transparent and feeding back advanced analytics to ensure improvement actions can be taken.

Benefits

Comprehensive AI Evaluations

Test and compare any AI system uniformly, revealing behavior patterns across diverse applications (data and model agnosticity)

Flexible Benchmarking

Assess against industry standards or set custom thresholds on the results of tests in order to parametrize expectations on technical metrics

Scalable
Testing

Equip AI experts with cost-efficient, streamlined and automated testing processes and out-of-the-box  tools, which remove redundant computations

Expedited
Rollouts

Proactively run models through automated tests relevant for internal policies or external regulations and access same-day feedback

Seamless Integration

Flexibly integrate this scalable testing engine in your current MLOps workflow or GRC landscape for effective quality assurance

Risk
Mitigation

Run technical tests required by guidelines or assess guardrails, including those designed to protect against prompt injection attacks

Data-Driven
Insights

Generate high-quality and pre-configured analytics to identify critical weaknesses and opportunities for targeted improvements

Confident Decision-Making

Make informed choices backed by thorough, standardized assessments, which are already sorted and shareable with broader teams

Unfamiliar with the full AI Trust Platform which PiCrystal powers?

How does PiCrystal work?

The Informal Version

PiCrystal tests AI models across numerous scenarios, even if you don’t have specific data to cover each case, to help ensure that the machine learning model aligns with the desired outcomes or behaviors.

Our component library allows you to estimate relevant annotations in your test data, transform data samples, and define the metrics you want to measure, so you can build a complete view of your model performance.

With PiCrystal, you can set up and scale tests to uncover where your model is effective, identify limitations, and diagnose potential weak spots. These insights are invaluable for creating model cards and reports, giving you a clear picture of your model’s strengths and boundaries.

Ready to learn more?