Braintrust
Enterprise AI evaluation, prompt playground, and continuous LLM monitoring
About Braintrust
Braintrust is an enterprise-grade AI evaluation, prompt engineering, and LLM observability platform built to help software teams safely iterate and deploy generative AI features to production. It bridges the gap between ad-hoc prompt tweaking and rigorous software engineering CI/CD workflows. With Braintrust, teams run automated evaluation benchmarks on every prompt change, comparing output quality, hallucination rates, and latency across multiple LLM versions before committing changes to production codebases.
The platform features an interactive collaborative prompt playground where non-technical product managers and engineers can experiment with system prompts against real customer test cases. Its runtime proxy captures production logs, auto-flags anomalies, and builds curated regression datasets from live traffic. Braintrust is designed with privacy-first architecture, supporting secure client-side proxying and encrypted evaluation pipelines trusted by high-growth startups and Fortune 500 enterprises.
Integrate the Braintrust SDK into your development workflow or CI/CD testing pipeline.
Curate golden test datasets representing representative user inputs and expected ground truth outputs.
Run automated evaluation suites comparing prompt variations and model providers (GPT-4o, Claude 3.5, Gemini).
Inspect scoring metrics (accuracy, relevance, toxicity, token spend) on the Braintrust web dashboard.
Deploy approved prompt versions directly via the Braintrust runtime API without redeploying application code.
Capabilities & Features
Common Use Cases
prompt-evaluation
ci-cd-testing
llm-observability
regression-testing
prompt-management
Frequently Asked Questions
What is Braintrust and how does it improve AI applications?
Braintrust is an AI evaluation and observability platform that helps teams test, benchmark, and monitor prompt changes in automated CI/CD pipelines to prevent production regressions.
Can non-technical team members use Braintrust?
Yes, Braintrust includes a collaborative web playground where product managers, designers, and domain experts can test prompts against real datasets without writing code.
Does Braintrust support CI/CD integration?
Yes, Braintrust provides native CLI and SDK hooks to run automated regression tests on every GitHub pull request.
Free Plan
Free tier with up to 1,000 evaluations/month, collaborative prompt playground, and basic tracing
Paid Plan
Team from $100/mo and Enterprise with custom dataset volume, self-hosted proxy, and SOC 2 security
Pros & Cons
Integrates AI evaluations directly into automated CI/CD testing pipelines
Collaborative prompt playground allows product managers and engineers to align on prompts
Transforms production logs into curated regression test datasets automatically
Supports custom programmatic scorers and LLM-as-a-judge evaluation frameworks
Enterprise-grade security with SOC 2 compliance and encrypted telemetry
Targeted primarily at professional engineering teams rather than casual solo builders
Team tier subscription starts at $100/mo for growing data volumes
Alternatives
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Open source LLM observability, tracing, and evaluation platform
Langfuse is an open-source LLM engineering and observability platform built for teams developing production-grade generative AI applications and autonomous multi-agent pipelines. It captures granular traces across token usage, prompt versions, latency bottlenecks, and retrieval accuracy, giving developers complete visibility into model behavior at runtime. By integrating seamlessly with major AI frameworks such as LangChain, LlamaIndex, LiteLLM, and the OpenAI SDK, Langfuse eliminates the guesswork from debugging complex agent execution trees. Developers can monitor production cost metrics, identify hallucinated responses, and run rigorous continuous evaluation suites on live traffic.
Portkey
Production AI gateway, load-balancing, and LLMOps control plane
Portkey is an enterprise-grade AI Gateway and LLMOps control plane designed to make production AI applications fast, reliable, and cost-efficient. By acting as a unified proxy between your applications and 250+ LLMs, Portkey handles automated provider fallbacks, load balancing, rate-limiting, and semantic caching with zero code changes. Engineering teams use Portkey to eliminate single-provider downtime risks (e.g. automatic failover from OpenAI to Anthropic during outages) while cutting inference latency and API costs by up to 40% through intelligent semantic caching.
Anthropic Console
Enterprise-grade AI for developers
The developer gateway to Claude models, offering advanced controls like prompt caching and Artifacts rendering via API.
Agno
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Agno (formerly Phidata) is a lightweight, ultra-fast Python framework engineered for building production-grade autonomous multi-agent systems with native memory, knowledge retrieval, and multimodal reasoning capabilities. It is designed to replace bloated agent frameworks with a pure, pythonic developer experience. Agno agents operate up to 10x faster than legacy orchestration libraries by eliminating unnecessary abstractions. With built-in support for vector databases (PgVector, Qdrant, Pinecone), structured output schemas, and agent-to-agent delegating protocols, developers can build complex autonomous assistants with under 20 lines of clean code.
Relevance AI
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Relevance AI is a platform designed to create AI workforces by combining LLM agents, tasks, and data pipelines. It provides an intuitive low-code workspace to build autonomous agents that execute multi-step operations.
LangChain
Build context-aware reasoning applications
The most popular framework for developing applications powered by large language models, including agents and RAG.
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