Giskard vs LangSmith

Giskard is an open-source and enterprise platform for automated red-teaming and evaluation of AI models and LLM agents, detecting vulnerabilities like hallucinations, prompt injections, biases, and robustness issues through continuous scanning and test suites. It differentiates with black-box testing, collaborative workflows for business and technical teams, and integration of domain knowledge for exhaustive, domain-specific tests. Typical buyers are AI engineering, security, and data science teams at enterprises in finance, manufacturing, public sector, and defense deploying production AI systems. The platform supports compliance via GDPR, SOC 2 Type II, and HIPAA features, and was recognized in Gartner's 2023 Market Guide for AI Trust, Risk and Security Management.

LangSmith is an LLM observability platform that provides tracing, monitoring, and evaluation for AI agents and LLM applications. It offers native tracing for agent frameworks, cost and latency tracking, online LLM-as-judge evals, custom dashboards, and alerts via webhooks or PagerDuty. Framework-agnostic with SDKs for Python, TypeScript, Go, Java, and OpenTelemetry support, it works with OpenAI, Anthropic, LlamaIndex, and custom stacks. Typical buyers are engineering teams building production LLM apps needing visibility into agent behavior, debugging failures, and performance optimization. Enterprise plans include self-hosted and BYOC options for data residency.LangSmith homepage Pricing