Laminar vs LangWatch

Laminar is an open-source, OpenTelemetry-native observability and debugging platform for AI agents. It traces LLM calls, tools, custom functions, and sub-agents as readable transcripts. Signals turn plain-language outcomes or failures into structured events across traces. Its debugger replays runs from cache to a selected point, while evaluations run against datasets locally or in CI to catch regressions. Laminar provides realtime traces, full-text search, raw SQL through its UI, CLI, or MCP, and custom dashboards. Integrations include OpenAI, Anthropic, Gemini, Cohere, LangChain, Pydantic AI, Claude Code, and Playwright. Deployment is available through managed cloud or self-hosting, including AWS or GCP with Helm charts. The Free plan is free with 1 GB data and seven-day retention. Starter costs $30 a month; Pro costs $150 a month.

LangWatch is an AI agent engineering platform for teams preparing agents for production. Simulations cover multi-turn conversations, tool use, recovery, and business outcomes before launch. Evaluations can run on datasets, production traffic, or in CI/CD workflows that gate merges. Traces show agent steps alongside cost, tokens, duration, errors, evaluations, and annotations. Integrations include Python and TypeScript SDKs, OpenTelemetry, REST ingestion, model providers, and frameworks such as LangGraph, LangChain, CrewAI, and DSPy. Voice-agent testing supports OpenAI Realtime, Gemini, ElevenLabs, Google Live API, Pipecat, WebSocket bots, and Twilio. Deployment options are managed cloud, self-hosted, and hybrid; self-hosting uses Docker Compose and the customer’s ClickHouse. LangWatch is open source under Apache 2.0. The Developer plan costs nothing and includes 50k events per month, 14-day data access, and two users. Growth costs €29 a month per core seat and includes 200k events. The trust center lists encryption, access controls, privacy features, and enterprise DPAs.