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Giskard

Open-source evals, red teaming and test generation for agentic systems.

Giskard builds an open-source (Apache-2.0) Python library for testing and evaluating agentic systems, alongside a commercial AI red-teaming and LLM security platform. Giskard v3 is a modular rewrite for dynamic, multi-turn agent testing: Giskard Checks for evals from simple assertions to LLM-as-judge, and giskard-scan for vulnerability scanning and RAG evaluation, built on giskard-core, giskard-llm and giskard-agents. It can wrap an LLM, a black-box agent or a multi-step pipeline. v2 remains available but is no longer actively maintained.

People

Featured

The de-facto standard toolkit for building LLM applications and agents.

LangChain makes the LangChain framework and LangGraph, the low-level orchestration standard for stateful, controllable agents, plus the LangSmith platform for tracing, evaluating and monitoring them in production.

~$75M raised

4 pros · 4 cons

Enterprise-grade evals, data and AI gateway.

Braintrust turns prompts and agent traces into testable datasets and CI, plus an inference gateway — helping teams measure whether harness changes actually improve agent quality.

4 pros · 4 cons

Observability and evaluation for AI — makers of OSS Phoenix.

Arize traces and evaluates LLM and agent systems in production; their open-source Phoenix tracer is a common instrumentation choice for agent harnesses that need to be debuggable.

4 pros · 5 cons

Connections

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Sources

  1. GitHub repository and README
  2. Giskard docs
  3. Giskard website