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The testing
platform for AI models

Protect your company against biases, performance & security issues in AI models.
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Open-Source
Listed by Gartner
AI Trust, Risk and Security
# Get started
pip install giskard[llm]
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Giskard - Open-source testing framework for LLMs & ML models | Product Hunt

Trusted by Enterprise AI teams

Why?

AI pipelines are broken

AI risks, including quality, security & compliance, are not properly addressed by current MLOps tools.
AI teams spend weeks manually creating test cases, writing compliance reports, and enduring endless review meetings.
AI quality, security & compliance practices are siloed and inconsistent across projects & teams,
Non-compliance to the EU AI Act can cost your company up to 3% of global revenue.

Enter Giskard:
AI Testing at scale

Automatically detect performance, bias & security issues in AI models.
Stop wasting time on manual testing and writing custom evaluation reports.
Unify AI Testing practices: use standard methodologies for optimal model deployment.
Ensure compliance with the EU AI Act, eliminating risks of fines of 3% of your global revenue.

Mitigate AI Risks with our holistic platform
for AI Quality, Security & Compliance

Giskard Open-Source

Python library for data scientists to get started with testing AI models in their development environment, for free.

Giskard Enterprise

Collaborative Hub to control all AI risks in one place and automate compliance, built for Al Quality, Security & Compliance at scale.
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TRY IT in COLAB
Giskard Open-Source

Easy to integrate for data scientists

In a few lines of code, identify vulnerabilities that may affect the performance, fairness & security of your LLM. 

Directly in your Python notebook or Integrated Development Environment (IDE).

import giskard‍
qa_chain = RetrievalQA.from_llm(...)
model = giskard.Model(
   qa_chain,
   model_type="text_generation",
    name="My QA bot",
    description="An AI assistant that...",
   feature_names=["question"],
)
giskard.scan(model)
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Giskard Enterprise

Collaborative AI Quality, Security & Compliance

Entreprise platform to automate testing & compliance across your GenAI projects.
Try our latest open-source release!

Evaluate RAG Agents automatically

Leverage RAGET's automated testing capabilities to generate realistic test sets, and evaluate answer accuracy for your RAG agents.
TRY RAGET

Who is it for?

AI Engineers
Heads of AI teams
AI Governance officers
You work on business-critical AI applications.
You work on enterprise AI deployments.
You spend a lot of time to evaluate AI models.
You’re preparing your company for compliance with the EU AI Act and other AI regulations.
You have high standards of performance, security & safety in AI models.

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

Head of Data
Emeric Trossat

Giskard's Red Teaming capabilities act like a health check for our AI chatbot, identifying vulnerabilities and providing actionable recommendations.

Hugues Even
Chief Data Officer
Hugues Even

Giskard has streamlined our entire testing process thanks to their solution that makes AI model testing truly effortless.

Corentin Vasseur
ML Engineer & Responsible AI Manager
Corentin Vasseur

Giskard Vision has become our go-to tool for testing our landmark detection models. It allows us to identify biases in each model and make informed decisions.

Alexandre Bouchez
Senior ML Engineer
Alexandre Bouchez

Join the community

Welcome to an inclusive community focused on AI Quality, Security & Compliance! Join us to share best practices, create new tests, and shape the future of AI standards together.

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All those interested in AI Quality, Security & Compliance are welcome!

All resources

Knowledge articles, tutorials and latest news on AI Quality, Security & Compliance

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Giskard-vision: Evaluate Computer Vision tasks

Giskard Vision: Enhance Computer Vision models for image classification, object an landmark detection

Giskard Vision is a new module in our open-source library designed to assess and improve computer vision models. It offers automated detection of performance issues, biases, and ethical concerns in image classification, object detection, and landmark detection tasks. The article provides a step-by-step guide on how to integrate Giskard Vision into existing workflows, enabling data scientists to enhance the reliability and fairness of their computer vision systems.

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Giskard integrates with NVIDIA NeMo

Evaluating LLM applications: Giskard Integration with NVIDIA NeMo Guardrails

Giskard has integrated with NVIDIA NeMo Guardrails to enhance the safety and reliability of LLM-based applications. This integration allows developers to better detect vulnerabilities, automate rail generation, and streamline risk mitigation in LLM systems. By combining Giskard with NeMo Guardrails organizations can address critical challenges in LLM development, including hallucinations, prompt injection and jailbreaks.

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Council of Europe - AI Treaty [1]

Global AI Treaty: EU, UK, US, and Israel sign landmark AI regulation

The Council of Europe has signed the world's first AI treaty marking a significant step towards global AI governance. This Framework Convention on Artificial Intelligence aligns closely with the EU AI Act, adopting a risk-based approach to protect human rights and foster innovation. The treaty impacts businesses by establishing requirements for trustworthy AI, mandating transparency, and emphasizing risk management and compliance.

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