Langwatchvs
Braintrust
Braintrust: Evaluations platform with comparable LLM testing capabilities
Langwatch
LLM engineering platform for testing and evaluating AI agents in production
Overview
What Langwatch does
Langwatch addresses a critical pain point in AI development: AI agents are tested manually and often break in production. The platform provides simulation-based evaluation that runs realistic user scenarios against agents to identify problems early. It features Langy, an AI-powered tool that automates test creation by converting product requirements into test scenarios, running simulations, scoring results, and generating pull requests with proposed fixes in a median of 14 minutes. Core capabilities include agent simulation testing with multi-turn conversations, LLM evaluation to measure response quality, full observability with OpenTelemetry-native tracing, and governance controls for model access and budget management. The platform supports multiple deployment options including cloud SaaS across EU, US, UK, and APAC regions, self-hosted Docker/Kubernetes, and hybrid setups where data stays on-premises.
What people use it for
- Continuous testing of AI agents before production deployment
- Automated test creation from product requirements
- LLM response quality evaluation and scoring
- Production agent monitoring and cost tracking
- Governance and access control for AI systems
Related searches
The honest half
Where it falls short
Concrete and checkable, so you can decide whether any of them matter to you. This is the half of a review a vendor will not write about Langwatch.
- Free plan limited to 50k events per month, restricting larger deployments
- Pricing in EUR may complicate budgeting for US-based teams
- Usage-based overage model can create unpredictable costs
- Self-hosted option requires DevOps expertise
Cross-shopped
What people choose instead of Langwatch
Each pairing was judged by two reviewers asking whether a buyer would genuinely weigh the two against each other. The ones that failed were deleted rather than published.
- LangwatchvsArize AI
Arize AI: MLOps platform with observability for AI systems
Pricing
What Langwatch costs
Taken from the vendor's own pricing page. Prices move, so check before you buy.
Developer
Free
- 50k events per month
- 14-day data access
- 2 users
- Community support
- No credit card required
Growth
€29 /mo
- 200k events per month included
- 5 EUR per 100k additional events
- 30-day data retention
- Unlimited lite-users
- Private support
Enterprise
On request
- Custom event limits
- Hybrid, self-hosted or on-premises deployment
- Custom SSO and RBAC
- Audit logs
- Dedicated support
Capabilities
Features
Agent simulation testing
Run realistic user scenarios against agents with multi-turn conversations
LLM evaluation
Measure response quality and accuracy across conversations
OpenTelemetry tracing
Full observability with every agent step traced and monitored
Langy AI Engineer
Automate test creation from requirements to pull requests
Governance controls
Set budgets, manage model access, and audit logs
Multiple deployment options
Cloud SaaS, self-hosted, or hybrid deployments available
Framework support
Works with LangGraph, LangChain, CrewAI, OpenAI Agents, and more
Answered, with sources
Questions people ask
Each answer names the page it came from, so you can check it rather than take our word for it.
Is there a permanent free tier?
Yes, Langwatch's Developer plan is free forever with 50k events per month, 14-day data access, 2 users, and no credit card required. It is specifically designed for individual developers prototyping AI applications.
SourceWhat is Langy and how does it save time?
Langy is an AI-powered tool that automates test creation. It converts product requirements into test scenarios, runs simulations, scores results, and generates pull requests with fixes in a median of 14 minutes.
SourceWhat frameworks does Langwatch support?
Langwatch works with LangGraph, LangChain, CrewAI, OpenAI Agents, AWS Bedrock, Azure OpenAI, Vertex AI, and other major LLM frameworks and platforms.
SourceKeep looking
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