PostHog is an open-source product platform that bundles analytics, session replay, feature flags, experiments, error tracking, logs, surveys, a data warehouse, data pipelines, and LLM observability into one system. It captures product data so that both people and AI agents can diagnose problems, find opportunities, and ship fixes.
Its self-driving mode turns signals in product data (errors, rage clicks, failed queries) into researched reports and pull requests that you review and merge. You can operate PostHog from Slack, the web app, a desktop app, or from an editor through its MCP server, which brings PostHog into Claude Code, Cursor, or any MCP-compatible agent.
Instrumentation happens through a JavaScript web snippet, SDKs for JavaScript, Next.js, React, Vue, React Native, Android, iOS, Flutter, Python, Node, PHP, and Ruby (with guides for Go, .NET, Django, Angular, WordPress, and Webflow), or the API. PostHog Cloud runs in US and EU regions; a Docker-based hobby deployment covers self-hosting at roughly 100k events per month.
Features
- Product analytics: autocaptured or manually instrumented events, analysed with visualisations or SQL
- Web analytics: a traffic dashboard covering conversion, web vitals, and revenue
- Session replay: recordings of user sessions on web and mobile apps
- Feature flags: roll out features to selected users or cohorts
- Experiments: measure the statistical impact of changes on goal metrics, including no-code setup
- Error tracking: capture exceptions, alert on them, and resolve issues
- Logs: ingest, search, and analyse log data next to product data
- Surveys: no-code templates or a custom survey builder
- Data warehouse: sync data from Stripe, HubSpot, and external warehouses and query it with product data
- Data pipelines: filter and transform incoming data, send it to 25+ destinations or webhooks, or batch export it
- AI observability: traces, generations, latency, and cost for LLM-powered apps
- Workflows: automate actions or send messages to users
