# PostHog

:hedgehog: PostHog is the leading platform for building self-driving products. Our developer tools – AI observability, analytics, session replay, flags, experiments, error tracking, logs, and more – capture all the context agents need to diagnose problems, uncover opportunities, and ship fixes. Steer it all from Slack, web, desktop, or the MCP.

Repository: https://github.com/PostHog/posthog
Canonical: https://ross.abutalabs.com/products/posthog
Homepage: https://posthog.com
Language: Python
License: NOASSERTION
License Family: other
Topics: analytics, python, react, javascript, typescript, ab-testing, experiments, feature-flags, session-replay, ai-analytics, cdp, data-warehouse, product-analytics, surveys, web-analytics
Last push: 2026-08-27T00:35:32+00:00
Link (homepage): https://posthog.com

## Health v2 (maintenance only)
Score: 95/100 (v2, computed 2026-09-03T02:39:23.370411+00:00)
- activity 99, release rhythm 87, longevity 100
- inputs: {"age_days": 2414, "days_push": 7, "days_rel": 6, "gap_med": 0, "n_releases_24m": 948}
- flags: no_license
- formula: round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10)

## Adoption (not part of the score)
Stars 39256, forks 3291 (observed 2026-08-28T04:12:07.789370+00:00)

## What it is
PostHog is an open-source product analytics platform combining product analytics, web analytics, session replay, feature flags, A/B experiments, error tracking, logs, surveys, and a customer data platform in one self-hostable or cloud-hosted suite. It also offers AI observability and 'self-driving' capabilities that turn product data signals into researched reports and pull requests, controllable via Slack, web, desktop, or MCP.

## Use cases
- track user behavior with event-based product analytics
- watch session replays to debug UX issues
- roll out features gradually with feature flags
- run A/B tests and measure statistical impact
- monitor web traffic and conversion funnels
- track and alert on application errors
- self-host a Google Analytics alternative
- analyze product data with SQL

## When to choose
- you want an all-in-one analytics, flags, and replay platform you can self-host
- you need autocapture analytics without manual instrumentation
- you want feature flags and experiments tightly integrated with analytics
- you need AI observability for LLM-powered products

## When to avoid
- you only need lightweight page-view counting without a data pipeline
- you cannot operate a resource-heavy Python/Docker stack and don't want the cloud offering
- you need strict per-event data residency controls the platform doesn't support

## Facets
- artifact type: application
- maturity: active
- function: analytics, monitoring, alerting, feature-flags, data-visualization, error-handling, logging, mcp, chatbot
- domain: analytics, developer-tools, web-development, artificial-intelligence, self-hosted
- platform: self-hosted, python
- tags: product-analytics, session-replay, feature-flags, ab-testing, web-analytics, surveys, data-warehouse, cdp, ai-observability, self-driving-products, web-server, docker, javascript, web

## Member repositories
- PostHog/posthog (main) score 95
- PostHog/posthog.com (docs) score 77

## Provenance
- Observed fields: from GitHub, fetched 2026-08-28T04:12:07.789370+00:00.
- Health v2: computed from the inputs above; adoption is never an input.
- Inferred fields (summary, facets, guidance): AI-extracted, prompt v1, taxonomy v1, on 2026-08-29T16:24:15.361660+00:00, confidence not recorded.
  - readme: https://github.com/PostHog/posthog (fetched 2026-08-28T04:12:07.789370+00:00, sha 951cfc0d4526)
  - homepage: https://posthog.com (fetched 2026-08-29T07:47:08.436597+00:00, sha 44136fa355b3)
- Data as of 2026-08-30T08:39:29.467469+00:00.