Giskard

Giskard is a black-box security and evaluation platform for conversational AI agents exposed through an API. It is most suitable for teams that need vulnerability findings tied to remediation, quality evaluation, and flexible deployment. The free local tooling is a credible starting point, while production use depends on whether Enterprise's custom-priced controls and support justify the commitment.

Overview

Giskard is designed to identify AI-agent weaknesses before deployment. Its testing scope includes prompt injection, data disclosure, inappropriate content, hallucinations, contradictions, and omissions. The Hub targets conversational text-to-text agents reachable through an API endpoint, so teams with other model shapes or access patterns should look elsewhere.

Each assessment produces a structured report with a deploy-or-fix verdict, ranked vulnerabilities, and functional scenarios. A passing agent receives a Giskard Label, giving teams a clear release signal rather than an unprioritized list of test output. Giskard also describes a remediation workflow: its team qualifies findings, discusses severity, prioritizes issues, opens tickets in the customer's workflow, and reruns tests to verify fixes.

Key features

Enterprise red teaming includes more than 50 automated adversarial probes, including multi-turn attacks, with techniques regularly updated. This provides broader attack coverage than a one-off prompt checklist and is aimed at teams operating agents in production.

Quality evaluation goes beyond safety scanning. Enterprise can generate domain-specific evaluation datasets, apply fine-grained RAG quality metrics, add custom metrics, and provide human-in-the-loop review interfaces. LLM-as-a-judge, safety evaluations, and CI/CD integration support repeatable checks in an engineering pipeline, while human review helps when automated scores cannot settle a domain-specific question.

Giskard Checks documents native SDK integrations for OpenAI, Google/Gemini, Anthropic, and Azure, with optional LiteLLM support for other providers. The open-source Python library runs behavioral tests under pytest and includes vulnerability and RAG-quality scans, making local and automated workflows practical. Its documentation does not provide a v3 equivalent for tabular classification and regression models, so teams needing those model checks should not assume parity with the LLM tooling.

Security controls include EU or US data residency and isolation, role-based access controls, audit trails, identity-provider integration, and a zero-training policy. Giskard states that data is encrypted at rest and in transit and cites GDPR, SOC 2 Type II, and HIPAA compliance. Enterprise adds SSO, versioning with audit trails, and scheduled email alerts.

Pricing

Free

The Free plan costs nothing. It includes the open-source library, local deployment, a basic LLM vulnerability scan using adversarial techniques from 2024, and a basic RAG evaluation report using correctness metrics. Community support and best-effort maintenance are included. This is well suited to individual developers and teams validating an approach locally, but it lacks the updated 50-plus-probe red-team package, collaboration, and dedicated support described for production use.

Enterprise

Enterprise has custom pricing and is intended for production LLM deployments. It combines AI-agent security red teaming, quality evaluation, integrations, collaboration, hybrid deployment options, and dedicated support with service-level agreements. Optional technical onboarding and consulting, plus on-premise, private-cloud, or SaaS deployment, make it appropriate for regulated or operationally mature teams. The trade-off is that budget and scope require a sales discussion rather than a published rate.

Platforms

Giskard supports API, Linux, self-hosted, and web environments. Enterprise deployment can be on-premise, in a private cloud, or delivered as SaaS; its team can help install Hub on-premise for sensitive workloads. The Free plan's local deployment favors developers who want control over execution and data.

Who it's for

Choose Giskard for conversational agents with an API endpoint when security testing must connect to ranked findings, tickets, retesting, and release decisions. It is a strong fit for teams combining adversarial testing with RAG and domain-quality evaluation, especially where residency, auditability, identity integration, or on-premise operation matters. It is less suitable for unsupported model types, teams seeking a transparent Enterprise price, or users who only need a lightweight standalone scanner.

Pros and cons

Pros

• Structured decisions: Deploy-or-fix verdicts, ranked vulnerabilities, scenarios, and a passing label turn test results into release evidence.
• Remediation follow-through: Finding qualification, ticket creation, prioritization, and reruns connect assessment to confirmed fixes.
• Broad production controls: Updated adversarial probes, custom metrics, human review, CI/CD integration, and enterprise identity and audit features cover operational needs.
• Flexible hosting: Local, self-hosted, private-cloud, SaaS, and on-premise options support different data constraints.

Cons

• Narrow Hub target: The main workflow is for conversational text-to-text agents reachable through an API.
• Free coverage is limited: The free scan uses adversarial techniques from 2024 and provides only basic RAG correctness reporting.
• Enterprise cost uncertainty: Production features have custom pricing, making comparison and budgeting harder.
• Model-scope gap: Tabular classification and regression models have no documented v3 equivalent in the open-source library.

Alternatives

Promptfoo is a better fit when you want a free Community plan with 10,000 red-team probes per month, broad provider integrations, and local or self-hosted execution.

DeepEval suits teams seeking a free, Apache 2.0-licensed open-source LLM evaluation framework with a local and CI/CD test runner.

Whisper is a free, locally installable open-source code-and-model package rather than a dedicated agent security workflow.

Confident AI is worth considering for a hosted evaluation service with a free tier limited to two seats, one project, and five test runs per week.

Galileo is an alternative for teams prioritizing hosted observability and analytics, with a Pro plan listed at $100 a month when billed yearly.

garak is a free open-source option for users who want a focused security-testing tool.

HELM is a free open-source Python framework with no paid plans listed.

Maxim AI is an alternative for teams wanting a free developer tier with up to three seats, one workspace, and 10,000 logs per month.

For broader category comparisons, see LLM Evaluation Tools, AI LLM Evaluation Tools, AI Red Teaming Tools, LLM Observability Tools, AI Agent Evaluation Tools, and AI Security Testing Tools.

Verdict

Giskard is a strong choice for organizations that need API-based conversational-agent security and quality checks connected to remediation, governance, and deployment control. Its free plan lowers the barrier to local evaluation, but teams should look elsewhere if they need broader model coverage or predictable production pricing without an Enterprise engagement.