Automations, described by what they do

15,351 working automation workflows. Every description is composed from the workflow's own steps: what starts it, which services it touches, whether it hands judgement to a model, and how much there is to read.

Browse the libraryBrowse by job

Cleaned of credentials and personal data. Ready to import.

Running now3 steps

Send daily Mailchimp subscriber reports to Slack

Waiting for a trigger
Workflows15,351working automations
Call a model7,615hand a step to AI
Services60apps they connect
Small5,286readable in one sitting

What they're for

17 kinds of job

The library

16 found

AllContentAlerts and monitoringData collectionIntegrationsLead generationResearch and reportingAI assistantsSchedulingMoney adminDocuments and filesChat assistantsCustomer supportE-commerceCRMHiringSetup and learningStrategy and planningPinecone ✕

Data collectionAINotion to Pinecone vector store integration with GeminiStarts on an event in a connected app · 8 stepsNotionPineconeData collectionAIAI-powered Asana task prioritization with OpenAI and PineconeStarts on a clock · 10 stepsAsanaPineconePostgresData collectionAISend personalized SaaS welcome emails with Stripe and PineconeStarts on an event in a connected app · 10 stepsGmailGoogle SheetsPineconeData collectionAIGuide students with RAG and OpenAIStarts on someone opening a chat with it · 14 stepsGoogle SheetsPineconeData collectionAIScrape and ingest web pages into a Pinecone RAG stackStarts on someone opening a chat with it · 15 stepsPineconeData collectionAICreate AI-ready vector datasets for LLMs with Bright DataStarts on an event in a connected app · 16 stepsPineconeData collectionAISynchronize MySQL database schemas to Pinecone with OpenAIStarts on an event in a connected app · 17 stepsMySQLPineconen8n data tableData collectionAIExport WordPress to Pinecone vector store with OpenAIStarts on a clock · 19 stepsPineconeData collectionAISmart chat assistant with OpenAI and Google SheetsStarts on someone opening a chat with it · 22 stepsGmailGoogle DriveGoogle SheetsPineconeData collectionAIServe a RAG chat backend for Next.js with OpenAI and RedisStarts on another system calling it · 23 stepsPineconePostgresRedisData collectionAIBuild AI-ready knowledge base from Outlook & NotionStarts on someone opening a chat with it · 25 stepsNotionOutlookPineconeData collectionAISync Notion knowledge base with Vapi and PineconeStarts on a clock · 25 stepsNotionPineconeData collectionAIAI email auto-responder system- AI RAG agent for email inboxStarts on an arriving email · 27 stepsGmailGoogle DocsGoogle DriveNotionData collectionAIScrape website with Gemini and Pinecone DatabaseStarts on an event in a connected app · 30 stepsGoogle DocsGoogle DrivePineconeData collectionAIBuild a Google Drive internal knowledge base with OpenAIStarts on another system calling it · 34 stepsGmailGoogle DriveGoogle SheetsPineconeData collectionAICentral AI agent of an IT company with Gemini and OpenRouterStarts on someone opening a chat with it · 39 stepsGoogle DrivePineconePostgres

Start small

A few you can read in one sitting

What we took out

Cleaned before anything was stored

These files carry more of whoever built them than is obvious. All of it is stripped, and every file was checked, not sampled. Where an author left a live document behind, it is replaced with the placeholder the careful ones used, so you can still see what belongs there.

Triggers

What starts them

  1. A clock4,166
  2. An event in a connected app3,946
  3. Another system calling it2,801
  4. An arriving email1,591
  5. Someone submitting a form1,545
  6. Someone opening a chat with it895
  7. A change in a Google Sheet216

Services

What they touch

Google Sheets5,229Gmail3,419Slack2,307Telegram1,809Google Drive1,540Email863Airtable554Google Calendar480Notion471RSS404Postgres306WhatsApp285

Read the workflows

Filter 15,351 automations by what they do, what they connect to and how big they are, and open the definition itself, ready to import.

Q&A

What are these?

Working automations: the definition of each, ready to import, with a description composed from its own steps.

Why are some descriptions unflattering?

Because they say what the workflow does. One that is four steps and a webhook is described as four steps and a webhook, so you can decide from the page whether it is worth your afternoon.

What was removed from the files?

Instance identifiers, canvas notes with personal links and email addresses, saved credential names, and live documents left in by their authors. Every file was checked, not sampled.

What do I need to run them?

A workflow automation tool that imports these definitions. Each imports as it is; you add your own credentials.