Data pipelines in PostHog Web

The PostHog web app is where you build pipelines and watch them run. Sources, transformations, destinations, and batch exports each get their own section, and every pipeline you create – whether from a template or written by hand – ends up as a Hog function you can open, edit, and test.

What you can do here

Link sources

Connect an external tool so its data syncs into PostHog on a schedule, or set up an incoming webhook to push events in yourself. Synced data lands in the data warehouse, where you can join it to events and persons. See sources for the full list of connectors.

Transform events during ingestion

Transformations run before an event is stored, so they're the right place to enforce a schema, redact a property, label events, or drop traffic you don't want to pay for. Transformations run in a defined order, which you can rearrange, and a separate event ingestion filtering view lets you block events at the edge without writing code.

Send data to destinations

Realtime destinations fire as events arrive – useful for alerts, CRM syncs, and ad platform conversions. Batch exports run on a schedule and are built for volume, which is what you want for S3, BigQuery, Snowflake, Postgres, Redshift, Databricks, and Azure Blob Storage. You can customize any destination by editing its underlying function.

Test, monitor, and debug

Each function has a test-invoke step that runs it against a real recent event and shows the exact request it would send, without delivering anything. Once it's live, per-function logs and metrics separate successful runs, failures, and events that were filtered out, so you can tell an empty filter apart from a rejecting destination. Event ingestion warnings surface problems that happen upstream of your pipelines.

Ask PostHog AI

PostHog AI works inside the pipeline editor – it's an interaction mode here, not a separate surface. Describe the function you want in plain language and it writes the Hog code, generates the input variables, and builds the event filters to go with it. You can then iterate on the result with follow-up instructions. See writing Hog functions with PostHog AI for prompts that work well.

Related

• Create and debug the same functions from your editor over MCP.
• Manage them programmatically with the API.
• Fix delivery problems with the troubleshooting guide.