Trusted by Individuals and Enterprises

"PixieBrix has solved one of our hardest operational problems - streamlining communication & product updates across support teams. Tracking and keeping everyone in the loop has yielded better agent performance, customer satisfaction & taken a huge burden off management."

Thatcher Foster

VP, Client Solutions

Top reasons to automate in the browser

Surface schema metadata, query history, and pipeline status in one sidebar without switching between warehouse and orchestration tabs

Create Jira or GitHub issues from any monitoring alert page with pre-filled error details, timestamps, and affected tables in one click

Pull data lineage and column definitions from your catalog directly into Confluence or Notion documentation pages

AI Copilot in the sidebar can summarize query logs, explain error traces, or draft incident postmortems from the current page

Clip SQL results, cost metrics, or performance stats from cloud consoles into Google Sheets without manual reformatting

Build reusable workflows your data team can share for common tasks like schema documentation or incident triage without writing custom scripts

Frustrations that cost your team hours every week

Constant tab switching between data warehouse consoles, orchestration UIs, monitoring dashboards, and issue trackers to debug pipeline failures
Manually copying SQL results, schema metadata, or error logs from data platform consoles into Jira tickets or Confluence documentation
No quick way to create an incident ticket from a monitoring alert without switching to the issue tracker and re-entering context by hand
Cross-referencing data lineage across multiple browser-based catalog and warehouse tools requires keeping many tabs open simultaneously
Repetitive documentation updates when schema changes require manually copying column definitions from the warehouse UI into wiki pages
Extracting query performance metrics or cost data from cloud consoles into spreadsheets requires tedious copy-paste formatting
Reviewing pull requests for pipeline code while needing to check the corresponding table schema in a separate warehouse tab

Chat with AI to create your first custom workflow

Extract the error details from this monitoring alert and create a ticket in my issue tracker with affected tables

File Pipeline Incident

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Pull the column definitions from this data warehouse table and update the schema documentation in my wiki

Document Schema Changes

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Summarize the query cost and performance metrics on this page and format them as a table for my spreadsheet

Summarize Query Costs

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Based on the alert history on this page, draft an incident postmortem with timeline, root cause, and action items

Draft Incident Review

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Summarize this stakeholder data request and create a ticket in my project tracker with priority and estimated effort

Triage Data Request

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Pull the upstream dependencies for the table on this page and list them with their last refresh timestamps

Check Pipeline Lineage

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Frequently Asked Questions

Who is PixieBrix for?

PixieBrix is designed for teams that want to move faster without heavy engineering effort. It is commonly used by support teams, operations teams, product teams, and technical teams who need to connect tools, reduce manual work, and ensure the right information reaches the right people at the right time.

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What is PixieBrix?

PixieBrix is a browser-based automation platform that lets you customize how the tools you already use work together. It allows teams to add context, automate workflows, and create guided experiences across apps like support tools, internal dashboards, and SaaS products without building or maintaining custom integrations.

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How does PixieBrix work?

PixieBrix works by layering automation directly into the browser. It can read data from the page you are viewing, connect to APIs, and trigger actions like sending messages, filling forms, or enriching data in real time. This lets teams automate workflows exactly where work is already happening.

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"PixieBrix has solved one of our hardest operational problems - streamlining communication & product updates across support teams. Tracking and keeping everyone in the loop has yielded better agent performance, customer satisfaction & taken a huge burden off management."

Thatcher Foster

VP, Client Solutions

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Datadog

Grafana

Confluence

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Chat with AI to create your first custom workflow

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