AI observability platform with Loop agent that automatically generates better prompts, scorers, and datasets from production data. Free tier available, Pro at $25/seat/month.
AI observability platform that monitors LLM applications and automatically optimizes prompts using production data patterns.
Braintrust is an AI development and testing platform that combines observability, evaluation, and automated prompt optimization through its Loop agent, with pricing starting free and Pro at $25/seat/month. It targets engineering teams of 3+ people building production LLM applications who need systematic quality assurance beyond basic monitoring. Based on our analysis of 870+ AI tools, Braintrust is the only AI observability platform that monitors LLM applications AND automatically fixes them. While Langfuse and Helicone track what happens, Braintrust's Loop agent generates better prompts from your production data.
This is the differentiator. Describe what's wrong ("chatbot responses are too formal"), and Loop analyzes your traces to generate 12 prompt variations designed to fix that specific issue. No manual prompt engineering required. The agent learns from your evaluation results and iteratively improves prompt quality based on real production data, replacing what typically takes 10-20 engineering hours per month of manual optimization work.
Manual prompt optimization costs 10+ engineering hours monthly at $100/hour = $1,000+. Braintrust Pro at $25/seat automates this — a 40x ROI for active teams.
Compared to the 4 other AI observability tools in our directory: vs Langfuse — Free, open-source, self-hosted monitoring. No automatic optimization. Pick Langfuse for budget monitoring, Braintrust for automated improvement. vs Helicone — $20/month for simple OpenAI tracking. Pick for basic monitoring without optimization needs. vs LangSmith — Best if all-in on LangChain ecosystem. Braintrust is model-agnostic and works with OpenAI, Anthropic, Google, and 20+ LLM providers.
Braintrust pays for itself when you're already spending engineering time on prompt optimization. The Loop agent does the work better and cheaper than manual engineering. Start with the free tier (1K eval rows/month) to test it on your data before committing to Pro at $25/seat.
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Buy Braintrust Pro ($25/seat) if you're manually optimizing prompts and spending $1K+/month in engineering time. Loop agent automates optimization better than manual engineering. Skip if you just need monitoring — Helicone ($20/month) or Langfuse (free) handle that cheaper.
Describe a quality issue in plain English (e.g., 'responses are too formal') and Loop analyzes your production traces to generate 12 candidate prompt variations targeting that specific problem. The agent learns from evaluation outcomes, so each cycle improves on the last rather than starting from scratch. This is the core differentiator versus every other observability tool in our directory.
Captures every LLM call with full input/output, latency, token costs, and metadata across OpenAI, Anthropic, Google, and 20+ providers. Traces are searchable and filterable, and become the raw material the Loop agent uses for optimization. Free tier supports 1K eval rows/month with 14-day retention; Pro is unlimited with 30-day retention.
Define automated quality scorers — accuracy, helpfulness, tone, factuality, custom business metrics — that run on every production trace or eval batch. Scorers can be LLM-as-judge, code-based, or human-rated, and feed back into Loop for targeted optimization. Catches regressions before they reach users and quantifies prompt changes objectively.
Curate evaluation datasets directly from production traces, marking real user interactions as test cases rather than relying on synthetic examples. Datasets version automatically and integrate with CI/CD pipelines for regression testing. This grounds evaluation in real user behavior and edge cases that synthetic tests typically miss.
Run multiple prompt variations or model providers in parallel and compare results across all your scorers in a single dashboard. Useful for vendor selection (OpenAI vs Anthropic vs Google), prompt iteration, and cost/quality trade-off decisions. Outputs are diff-able at the row level so you can see exactly where two configurations diverge.
$0
$25/seat/month
Custom
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