Braintrust vs PyRIT

Braintrust is an observability platform for teams running AI agents in production. It lets teams inspect agent traces and tool calls while tracking latency, cost, and quality in real time. Users can evaluate datasets, compare prompts and models, and score outputs with LLMs, code, or human reviewers. Discovery tools surface patterns in production traces to help investigate agent behavior, and the Loop agent can run evaluations, generate test cases, and iterate on prompts autonomously. Braintrust lists native SDKs for Python, TypeScript, Go, Ruby, C#, and more, and its MCP server lets coding agents query logs, run evaluations, and update prompts from an IDE. Security options listed include SSO, RBAC, and hybrid deployment; Braintrust states that it is SOC 2 Type II certified and GDPR and HIPAA compliant. Starter is free, with 1 GB processed data, 10,000 scores, and 14-day retention. Pro costs $249.00 per month; Enterprise pricing is custom.

PyRIT is a free, MIT-licensed framework for security professionals and engineers assessing risks in generative AI systems. It supports single-turn and multi-turn red-team strategies such as Crescendo, TAP, and Skeleton Key. Scenario evaluations can be repeated across hundreds of objectives, including content harms, psychosocial risks, and data leakage. CoPyRIT provides a web interface for interacting with AI systems, recording findings, and collaborating with a team. Documented targets include OpenAI, Azure, Anthropic, Google, HuggingFace, custom HTTP endpoints and WebSockets, and web apps tested with Playwright. PyRIT stores conversations, scores, and attack results in SQLite or Azure SQL and can export results. Scoring supports true/false, Likert, classification, and custom scorers, including LLM-based and Azure AI Content Safety methods. Scanner, GUI, Framework, pyrit_scan, and pyrit_shell modes are documented. Installation is available through Docker, pip, or uv, with Python 3.13 recommended locally.