Overview

PostHog is the leading open-source platform for building truly "self-driving" products. It equips you with a comprehensive suite of developer tools designed to provide complete context for diagnosing issues, identifying growth opportunities, and shipping improvements rapidly. From AI observability and product analytics to session replay, feature flagging, and error tracking, PostHog empowers teams to proactively steer product development.

Key Features

• AI Observability: Gain deep insights into your LLM-powered applications, tracking traces, generations, latency, and costs.
• Product & Web Analytics: Understand user behavior with event-based analytics, visual dashboards, and GA-like web traffic monitoring.
• Session Replays: Watch real user interactions to pinpoint bugs and understand user journeys.
• Feature Flags & Experiments: Safely roll out new features, A/B test changes, and measure their impact with no-code options.
• Error Tracking & Logs: Proactively monitor and resolve errors, and analyze log data alongside product insights.
• Surveys: Gather user feedback through customizable no-code survey templates.
• Data Integrations & Pipelines: Sync data from external tools and transform incoming data in real-time.
• Self-Driving Mode: Automatically convert product signals (like errors and rage clicks) into actionable reports and pull requests.
• Unified Control: Manage PostHog features and insights directly from Slack, web interfaces, desktop applications, or via the MCP.
• Generous Free Tier: Utilize a robust monthly free tier for all core tools, with transparent pricing for scaling.

Typical Use Cases

• Accelerated Bug Resolution: Quickly identify, diagnose, and fix user-reported issues by correlating session replays, error logs, and user behavior.
• Data-Driven Product Development: Make informed decisions about new features and improvements by analyzing user engagement, conversion funnels, and experiment results.
• Optimized Feature Rollouts: Mitigate risk and gather feedback by gradually releasing new features to specific user segments using feature flags.
• Enhanced User Experience: Understand and address friction points in the user journey by watching session replays and analyzing user interaction patterns.
• AI Application Monitoring: Ensure the performance, cost-effectiveness, and reliability of your AI-powered features.
• Proactive Problem Solving: Leverage AI observability and automated workflows to anticipate and resolve issues before they impact users.