Braintrust vs LangSmith: Observability, Prompts & Evals Comparison
Compare Braintrust and LangSmith side by side. Both are tools in the Observability, Prompts & Evals category.
Updated March 9, 2026
The short answer
Choose Braintrust if custom-built Brainstore database optimized for AI data with fast full-text search and low latency.
Choose LangSmith if deep integration with LangChain framework provides unmatched observability for LangChain applications.
Want to compare Braintrust and LangSmith on your own traffic?
Respan lets you trace LLM and agent calls across any model or framework, A/B test prompts on production traffic, and route requests across 250+ models through one gateway. Free tier covers 10K traces per month. Setup in 5 minutes, no credit card.
Quick Comparison
| Category | Observability, Prompts & Evals | Observability, Prompts & Evals |
| Pricing | Freemium | Freemium |
| Best For | AI teams who need a unified platform for logging, evaluating, and improving LLM applications | LangChain developers who need integrated tracing, evaluation, and prompt management |
| Website | braintrust.dev | smith.langchain.com |
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Pros & Cons: Braintrust vs LangSmith
- +Custom-built Brainstore database optimized for AI data with fast full-text search and low latency
- +Framework agnostic with native SDKs for multiple languages and no vendor lock-in
- +Comprehensive security and compliance certifications including SOC 2 Type II, GDPR, and HIPAA
- +AI-assisted Loop Agent for automated optimization of prompts and evaluations
- +Strong backing with $80M Series B funding and customers including Vercel, Notion, Coursera, and Dropbox
- −Relatively new platform founded in 2022, less mature than some competitors
- −Pro plan at $249/month may be expensive for smaller teams or individual developers
- −Limited public information about advanced features and customization options
- +Deep integration with LangChain framework provides unmatched observability for LangChain applications
- +Comprehensive evaluation capabilities with custom metrics and automated regression testing
- +Excellent tracing UI with detailed step-by-step execution visualization
- +Strong dataset management and annotation workflows for human feedback
- −Tight coupling to LangChain ecosystem limits flexibility for non-LangChain applications
- −UI scalability issues reported when working with very large datasets
- −Production testing limitations - relies primarily on production logs for test datasets
- −SaaS-only deployment with no self-hosting option may not suit all enterprise requirements
Pricing: Braintrust vs LangSmith
- · 5,000 traces per month
- · 14-day retention
- · One seat
- · Basic evaluations
- · 100,000 traces (overage ~$0.50 per 1,000)
- · 400-day retention
- · Full evaluations
- · Custom dashboards
- · Custom trace volumes
- · Custom retention policies
- · SSO
- · Dedicated support
When to Choose Braintrust vs LangSmith
- Iterating on prompts with real production data
- Running evaluations across model versions
- Building golden datasets from production traffic
- Debugging LangChain and LangGraph applications
- Prompt iteration and A/B testing
- LLM output evaluation and scoring
About Braintrust
Braintrust is an AI observability and evaluation platform that helps teams build, monitor, and improve AI applications in production. The platform enables users to turn production traces into evaluations, compare prompts and models, and improve quality with every release. Built on a custom database called Brainstore designed specifically for AI data complexity, Braintrust provides real-time trace inspection, performance monitoring for latency, cost, and quality, along with automated alerts. The platform features Loop Agent for AI-assisted optimization of prompts, scorers, and datasets, and offers framework-agnostic native SDKs for Python, TypeScript, Go, Ruby, and C# with no vendor lock-in. Braintrust is SOC 2 Type II, GDPR, and HIPAA compliant with SSO/SAML integration and granular role-based access control.
About LangSmith
LangSmith is LangChain's observability and evaluation platform for building production-grade LLM applications. Founded in July 2023 by Harrison Chase and Ankush Gola as part of the LangChain ecosystem, LangSmith provides comprehensive tracing of every LLM call, chain execution, and agent step with detailed visibility into inputs, outputs, latency, token usage, and cost. The platform includes annotation queues for human feedback, dataset management for systematic evaluation, and regression testing capabilities for prompt changes. With over 1 million developers using LangChain products globally, LangSmith has become the go-to debugging and monitoring tool for teams building with the LangChain framework, serving major enterprises including Klarna, LinkedIn, Replit, GitLab, Elastic, and Cisco.
What is Observability, Prompts & Evals?
Tools for monitoring LLM applications in production, managing and versioning prompts, and evaluating model outputs. Includes tracing, logging, cost tracking, prompt engineering platforms, automated evaluation frameworks, and human annotation workflows.
Browse all Observability, Prompts & Evalstools →Other Observability, Prompts & Evals Tools
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