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LLM Evaluation
Continuously enrich your golden dataset
Giskard provides comprehensive security and quality scans that automatically enrich your test dataset.
By continuously running the scan, you can add detected vulnerabilities to your golden dataset and ensure your golden dataset remains exhaustive and up-to-date.
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Align testing with business context
Synthetic test generation alone isn't enough—you need to transform real human interactions into tests.
Giskard makes it easy to involve business experts in your testing process: add policies, establish ground truths, qualify failures with tags, and collaborate on test cases.
Turn business knowledge into actionable tests with the most accessible testing platform available.
Run evaluations & prevent regressions
Execute test suites through our intuitive UI or Python SDK.
Compare different versions of your AI agents to prevent regressions and maintain quality standards.
With Giskard, you have complete control over your LLM-as-a-judge setup, customizing it to meet your specific evaluation needs.
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Get alerts when new risks arises
Generate comprehensive reports from your LLM evaluation results that automatically surface critical issues affecting your business.
Export actionable reports designed specifically for compliance, risk, and product teams to drive informed decision-making.
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Why AI Security teams trust us
Prevent AI failures
We detect LLM vulnerabilities before they impact agents, unlike reactive tools that only alert you after problems occur in production.
For regulated industries
Built for banking, insurance, and other regulated sectors where AI failures carry significant compliance and reputational risks.
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Exhaustive testing
Testing for hallucinations, contradictions, and business compliance issues that traditional LLM evaluation frameworks miss.
FAQ
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- Automated Vulnerability Detection:
Giskard not only tests your AI, but also automatically detects critical vulnerabilities such as hallucinations and security flaws. Since test cases can be virtually endless and highly domain-specific, Giskard leverages both internal and external data sources (e.g., RAG knowledge bases) to automatically and exhaustively generate test cases. - Proactive Monitoring:
At Giskard, we believe itʼs too late if issues are only discovered by users once the system is in production. Thatʼs why we focus on proactive monitoring, providing tools to detect AI vulnerabilities before they surface in real-world use. This involves continuously generating different attack scenarios and potential hallucinations throughout your AIʼs lifecycle. - Accessible for Business Stakeholders:
Giskard is not just a developer tool—itʼs also designed for business users like domain experts and product managers. It offers features such as a collaborative red-teaming playground and annotation tools, enabling anyone to easily craft test cases.
Giskard employs various methods to detect vulnerabilities, depending on their type:
- Internal Knowledge:
Leveraging company expertise (e.g., RAG knowledge base) to identify hallucinations. - Security Vulnerability Taxonomies:
Detecting issues such as stereotypes, discrimination, harmful content, personal information disclosure, prompt injections, and more. - External Resources:
Using cybersecurity monitoring and online data to continuously identify new vulnerabilities. - Internal Prompt Templates:
Applying templates based on our extensive experience with various clients.
Giskard can be used before and after deployment:
- Before deployment:
Provides comprehensive quantitative KPIs to ensure your AI agent is production-ready. - After deployment:
Continuously detects new vulnerabilities that may emerge once your AI application is in production.
Yes! After subscribing to the Giskard Hub, you can opt for support from our LLM researchers to help mitigate vulnerabilities. We can also assist in designing effective safeguards in production.
The Giskard Hub supports all types of text-to-text conversational bots.
Giskard operates as a black-box testing tool, meaning the Hub does not need to know the internal components of your agent (foundational models, vector database, etc.).
The bot as a whole only needs to be accessible through an API endpoint.
- Giskard Open Source → A Python library intended for developers.
- LLM Hub → An enterprise solution offering a broader range of features such as:
- A red-teaming playground
- Cybersecurity monitoring and alerting
- An annotation studio
- More advanced security vulnerability detection
For a complete overview of LLM Hub’s features, follow this link.
Yes, you can easily install the Giskard Hub on your internal machines or private cloud.
The Giskard Hub is available through annual subscription based on the number of AI systems.
For pricing details, please follow this link.
Ready to prevent AI failures?
Start securing your LLM agents with continuous red teaming and testingthat detects vulnerabilities before they hit your LLM Agents.