Giskard vs Project Moonshot
Giskard
giskard.aiProject Moonshot
aiverifyfoundation.sgSide by side
| Figure | Giskard | Project Moonshot |
|---|---|---|
| Price from | Free | Free |
| Free plan | Yes | Yes |
| Free trial | — | — |
| Open source | Yes | — |
| Web | Yes | Yes |
| Windows | — | Yes |
| macOS | — | Yes |
| Linux | Yes | Yes |
| API | Yes | Yes |
| Self-hosted | Yes | Yes |
| Plans published | 4 | 1 |
| Spec score · AI Security Testing Tools | 8.6 (#5) | 8.3 (#8) |
| Custom evaluations | Professional includes domain-specific dataset generation, fine-grained RAG metrics, customizable checks and interoperability with other evaluation platforms. | Users can create recipes using their own datasets, optional prompt templates, evaluation metrics, and grading scales. |
| Founded | 2021 | 2024 |
| Integrations | The earlier product description lists compatibility with Hugging Face, MLflow, Weights & Biases, PyTorch, TensorFlow and LangChain. | Users can configure connections to their LLMs and create custom connector endpoints through the Web UI or CLI guides. |
| Purpose | Giskard describes its platform as a way to find vulnerabilities in AI agents before they reach production. | Project Moonshot is an open-source toolkit for testing the safety and reliability of LLMs and LLM applications through benchmarking and red teaming. |
| Support | The Free plan includes community support and best-effort maintenance; the Enterprise plan lists dedicated support with SLAs and optional technical onboarding and consulting. | The Moonshot FAQ directs users who need more help to raise an issue on GitHub. |
Plans
Giskard
- FreeFree
- Open-sourceFree
- EnterprisePriced on request
- ProfessionalPriced on request
In their own words
Giskard
Giskard provides tools for assessing AI agents before production, with coverage for prompt injection, data disclosure, inappropriate content, hallucinations, contradictions, and omissions. Its Hub performs black-box testing of conversational text-to-text agents available through an API endpoint. An assessment produces a structured report with a deploy-or-fix verdict, ranked vulnerabilities, and functional scenarios; passing agents receive a Giskard Label. Giskard describes a remediation process in which its team qualifies findings, discusses severity, prioritizes issues, opens workflow tickets, and reruns tests to check fixes. Enterprise evaluation options include adversarial probes, domain-specific datasets, RAG quality metrics, customizable metrics, and human review interfaces. Deployment choices include on-premise, private cloud, and SaaS. Giskard lists EU or US data residency, access controls, audit trails, identity-provider integration, encryption, and a zero-training policy, alongside GDPR, SOC 2 Type II, and HIPAA compliance. The free plan includes a local open-source library, basic vulnerability scanning and RAG evaluation, community support, and best-effort maintenance.
Project Moonshot
Project Moonshot is an open-source toolkit for evaluating the safety and reliability of large language models and applications. It runs benchmark tests using open-source datasets and metrics, and generates adversarial prompts to probe possible vulnerabilities and misuse. Users can build custom evaluations with their own datasets, optional prompt templates, metrics, and grading scales. Results appear in interactive HTML reports and downloadable raw JSON. Moonshot provides a Web UI, interactive command-line interface, library APIs, and Web APIs, with configurable connections to model providers including OpenAI, Anthropic, Together, and Hugging Face. Users can also create connectors for other models or applications hosted on custom servers. The toolkit implements benchmarks recommended in IMDA’s Starter Kit for safety testing LLM-based applications. Moonshot is free beta software under Apache License 2.0. Installation uses pip and requires Python 3.11; the Web UI additionally requires Node.js 20.11.1 LTS or later, and test assets are needed to run tests. The installation guide recommends Chrome for the Web UI and notes possible installation difficulties on x86 Macs with moonshot-data dependencies.