The testing
platform for AI models
Protect your company against biases, performance & security issues in AI models.
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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Trusted by leading 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 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.
Try our latest 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 RAGETWho 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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