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Quality Alignment
for AI models

Eliminate risks of AI incidents in production
Built in Europe 🇫🇷🇪🇺

Documentation

Trusted by Modern ML Teams

Emeric Trossat's picture, Head of Data at Webedia

Giskard really speeds up input gatherings and collaboration between data scientists and business stakeholders!

Emeric TROSSAT

Head of Data

Giskard has become a strong partner in our purpose for ethical AI. It delivers the right tools for releasing fair and trustworthy models.

Arnault Gombert

Head of Data Science

Giskard enables to integrate Altaroad business experts' knowledge into our ML models and test them.

Jean MILPIED

Data Science Manager

Giskard allows us to easily identify biases in our models and gives us actionable ways to deliver robust models to our customers.

Maximilien Baudry

Chief Science Officer

Product workflow

Deliver ML products, better & faster.
Become a ML superhero.

Integrate

API for any Python model: PyTorch, TensorFlow, Transformers, sklearn, etc.

Evaluate

Collaborate with business stakeholders with direct feedback & discussion

Test

Exhaustive test suites, backed by State-of-the-Art ML research.

Automate

Protect your ML models against the risk of regressions, drift and bias.

Check out our features

All use cases in one place

Listed by Gartner

Giskard was listed by Gartner as a representative vendor in the "Market Guide for AI Trust, Risk and Security Management"

MORE DETAILS

All resources

Thought leadership articles about AI Quality: Risk Management, Robustness, Efficiency, Reliability & Ethics

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Giskard 1.4 is out! What's new in this version? ⭐

With Giskard’s new Slice feature, we introduce the possibility to identify business areas in which your AI models underperform. This will make it easier to debug performance biases or identify spurious correlations. We have also added an export/import feature to share your projects, as well as other minor improvements.

Robot reading a newspaper generated by open-source generative AI model ControlNet and Stable Diffusion

How to evaluate and load a PyTorch model with Giskard?

This tutorial teaches you how to upload a PyTorch model (built from scratch or pre-trained) to Giskard, and identify potential errors and biases.

Ready. Set. Test!
‍Get started today