Giskard vs HELM

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.

HELM is an open-source Python framework for evaluating foundation models, including large language and multimodal systems. It supplies standardized datasets and benchmarks such as MMLU-Pro, GPQA, IFEval, and WildBench, with a unified interface for models from providers including OpenAI, Anthropic, and Google. Evaluations can examine accuracy, efficiency, bias, and toxicity, and can include custom metrics, LLM-as-a-judge checks, safety evaluations, and human review workflows. Users can configure private checkpoints or model servers, run inference locally, or send requests to an API. A web interface displays individual prompts and responses, while leaderboards compare models and benchmarks across areas such as medicine, finance, multilinguality, and world knowledge. HELM can reproduce published evaluation results and documents commands for running benchmarks, summarizing results, and starting a local server. It is free, Apache-2.0 licensed, and entered maintenance mode on June 1, 2026.