Giskard Overview, Features & Pricing (2026)
Overview
Giskard helps teams continuously test and harden LLM-based conversational agents before and after deployment. It automates test generation and execution to reveal hallucinations, bias, and security weaknesses across model updates. The platform offers role-based access, data residency options, and encryption to align with compliance needs. Engineers and product or security teams can run checks via a web UI or a Python SDK and turn findings into reproducible test suites.
Use cases
- Validate conversational agents before production release to reduce user-facing errors.
- Continuously monitor deployed models for hallucinations, data leaks, and performance regressions.
- Assess models for bias and fairness during iterative updates.
- Run security-focused tests to detect prompt injection and information exposure risks.
How it helps
- Reduces time to detect and fix model failures by automating repeatable tests.
- Improves output reliability and user trust through continuous quality checks.
- Supports cross-team collaboration with review dashboards and shared test suites.
Key features
- Continuous automated tests that surface hallucinations and regressions to cut troubleshooting time.
- Automatic conversion of findings into reproducible test suites to prevent regressions.
- Human-in-the-loop dashboards for cross-team review and fast approvals.
- Policy and access controls, data residency options, and encryption to meet Cybersecurity requirements.
- Programmatic execution via Python SDK and scheduling for CI/CD integration.
Pricing
Paid plans are available. Check the official site for current details.
Why to choose Giskard?
Giskard combines automated LLM testing with compliance-focused controls such as RBAC and data residency, enabling teams to find and fix model failures before they reach users.
