Give your agents the full context

Your context warehouse combines data storage and tooling with no pipelines to maintain, optimized for agents to use.

  • Store product and business data
  • Transform, query, and model
  • Data-driven self-driving development

Built for data engineers, loved by product teams

Data engineers

Build complex models and transformations that need your expertise, not plumbing.

  • Set up CDC pipelines from Postgres, MySQL, and other sources
  • Define and version core metrics so every team is working from the same numbers
  • Build and manage reverse ETL syncs to keep downstream tools up to date
  • Write transformation logic that enriches events with data from other systems
  • Query billions of rows without managing a cluster
  • Flexibility to use PostHog's full context warehouse or bring your own tools

Product engineers

Your data is already in PostHog. Query it, use it in experiments, and ship against it without waiting on the data team.

  • Sync external data sources and query them alongside your product events
  • Build experiment cohorts from warehouse data without creating a custom pipeline
  • Use PostHog AI to write SQL when you don't want to

Better data in, better AI out

Start with data you trust

AI products don't fail because the model is bad. They fail because the data feeding them is incomplete, inconsistent, or stuck in a tool it can't reach.

PostHog's context warehouse gives your AI features a foundation that works: clean event data, business context from your other tools, and full data ownership.

Start with data you trust

The stack that grows with you, not one you grow out of

The data you need on day one looks nothing like the data you need at scale. Start with what a small team needs and add capability as you grow into it.

Just launched
Getting traction
Scaling up
Data in
Send Events from your product
Sync Stripe and your CRM
Custom sources and transformation logic
Storage
Data stored by PostHog
Managed Warehouse, basic queries
Managed Warehouse, advanced modeling
Data out
Use PostHog Product Analytics
Create Cohorts from combined data
Reverse ETL to your whole stack
AI
Ask PostHog MCP to set up your tools
Use PostHog AI to query your data
Get PostHog Code to self-drive your development

No migration, re-instrumentation, or switching tools because you scaled out of them. If you really want to, we give you the credentials to directly access your data store to bring your own tools or export your data.

What's in your context warehouse

Use PostHog as the full context layer for your product, or mix and match with your own tools.

Get started

Your first data source is free to connect. So is your second. By the time you've connected your third, you'll stop thinking about your stack entirely, which is the whole point.

Get Started

Not using PostHog? Sign up

FAQ

Yes. You can query your existing Snowflake, BigQuery, or Redshift data inside PostHog without moving it. PostHog works alongside your current setup, or replaces parts of it, up to you.

You can migrate to PostHog's pipelines, or run them in parallel while you figure out what to move. The integrations overlap heavily, and switching is less painful than it sounds.

The data warehouse is free for your first 1M rows/month then from $0.000015/row (historical syncs are always free). Data pipelines are free for 10K events then from $0.0005/event, batch exports free for 1M rows then from $0.000015/row, and PostHog AI gives 500 free credits then $0.01/credit. See a full breakdown at posthog.com/pricing.

Your PostHog data stays in PostHog Cloud (EU or US region, your choice). When you sync external sources into the warehouse, that data is stored in PostHog's managed infrastructure. Full details in the docs.

Natively. Warehouse data can power cohorts used in experiments and flags. Pipeline data flows directly into analytics. Trino queries run on the same dataset your dashboards use. There's no separate sync to set up.

Warehouse sources and PostHog product events feed the context warehouse – an S3 data lake partitioned per org, a DuckLake catalog, and a single-tenant Trino in a Firecracker MicroVM – which in turn serves the Postgres wire protocol, analytics and experiments, AI agents, and endpoints

No. Ask questions in plain English and PostHog AI writes the SQL for you against your schema. If you do know SQL, the editor is right there and supports HogQL or standard SQL. Most product engineers start with plain English and drop into SQL when they want precise control.

You can do it yourself. Connecting a source is a few clicks, and your product events are already in PostHog. Data engineers are great for complex modeling and transformation logic, but you don't need to wait to hire one to sync a source, query it, or use it in a flag.

Product events are available immediately, no sync step. Synced sources like Stripe or your CRM refresh on a schedule, so there's a short delay on those. Once data is in the warehouse it can power cohorts, feature flags, and experiments natively without a separate pipeline to build to move it into the product.

Yes, sync a source like Stripe or Postgres, and you can join a revenue column to a signup event without moving data between tools or standing up your own ETL. It all lives in one warehouse.

Through the PostHog MCP. Point an agent (PostHog's, Claude Code, Cursor, whatever you're running) at the PostHog MCP and it can query your data directly. Or take any model or SQL query and expose it as a stable API endpoint your product or an agent calls, so the warehouse becomes something agents read from, not just a place dashboards pull from.

You set the boundaries. Access follows your existing PostHog permissions, and when an agent acts on your data, like opening a PR, you can review it before anything ships. Nothing self-drives past a checkpoint you haven't approved.