Giskard - AI Tool Features, UI & Interface Overview

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

  1. Validate conversational agents before production release to reduce user-facing errors.
  2. Continuously monitor deployed models for hallucinations, data leaks, and performance regressions.
  3. Assess models for bias and fairness during iterative updates.
  4. 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.