The testing
platform for AI models
Protect your company against biases, performance issues & security vulnerabilities in AI models. In <10 lines of code.
From tabular models to LLMs
From tabular models to LLMs
Listed by Gartner
AI Trust, Risk and Security
# Get started
pip install giskard[llm]
pip install giskard[llm]
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You can copy code here
Trusted by leading AI teams
Why?
AI pipelines are broken
MLOps tools don’t cover the full range of AI risks: robustness, fairness, efficiency, security, etc.
AI/ML teams spend weeks manually creating test cases, writing reports, and enduring endless review meetings.
AI Testing practices are siloed and inconsistent across projects & teams.
Non compliance to the EU AI Act can cost up to 3% of your 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 Library
Open-Source
Open-source Python library to identify & control risks in ML models and LLMs automatically, with a complete test coverage of performance, ethics & security metrics.
Giskard Hub
Enterprise Hub for teams to collaborate on top of the open-source library, with compliance dashboards, debugging, human feedback, explainability and secure access controls.
Giskard Library
Open-source & easy to integrate
In a few lines of code, identify vulnerabilities that may affect the performance, fairness & security of your model.
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)
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 Hub
Collaborative AI Quality, Security & Compliance
Entreprise platform to test, debug & explain your AI models collaboratively.
Who is it for?
Data scientists
ML Engineers
AI Governance officers
You work on business-critical AI applications.
You spend a lot of time to evaluate AI models.
You want to work with the best Open-source tools.
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.
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!
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