Giskard vs LangSmith
A side-by-side comparison of two LLM Evaluation AI agents — to help you pick the right one.
Giskard
Giskard is an open-source library designed for testing and evaluating large language model (LLM) applications, with a focus on Retrieval-Augmented Generation (RAG) systems. It provides tools to assess model robustness, fairness, and performance, helping developers identify and mitigate issues in LLM outputs.
LangSmith
LangSmith is a platform integrated with the LangChain framework, designed for evaluating, monitoring, and collaborating on LLM applications. It supports human-in-the-loop workflows, logging, and performance tracking for LLM-based systems.
| Giskard | LangSmith | |
|---|---|---|
| Category | LLM Evaluation | LLM Evaluation |
| Open source | Yes | Not publicly specified |
| Self-hostable | Yes | Not publicly specified |
| Skill level | Intermediate | Intermediate |
| Pricing | Open Source | Paid |
Giskard: what it solves
It solves the challenge of systematically evaluating and improving the reliability and safety of LLM applications, particularly in complex workflows like RAG.
LangSmith: what it solves
It streamlines the evaluation and iterative improvement of LLM applications by providing tools for logging, monitoring, and human feedback integration.