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

34 found

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

Data collectionAIDemand forecasting with OpenAI and PostgresStarts on an event in a connected app · 8 stepsPostgresData collectionAIAI-powered Asana task prioritization with OpenAI and PineconeStarts on a clock · 10 stepsAsanaPineconePostgresData collectionAIAI-powered customer feedback analyzer with OpenAI and PostgresStarts on another system calling it · 10 stepsPostgresData collectionAIAI-driven inventory management with OpenAI and ERPStarts on a clock · 12 stepsEmailPostgresData collectionAIAI agent that updates its own rules to modify behaviorStarts on someone opening a chat with it · 13 stepsGoogle SheetsPostgresData collectionAIProduct concept to 3D showcase with DALL-EStarts on another system calling it · 16 stepsPostgresData collectionAIAI study assistant with RAG and DriveStarts on someone opening a chat with it · 17 stepsGoogle DrivePostgresSupabase vectorsData collectionAIGenerate Complete Database Schemas with ClaudeStarts on someone submitting a form · 20 stepsPostgresData collectionAITriage emergency patients with OpenAIStarts on someone opening a chat with it · 20 stepsPostgresData collectionAIAutomate customer retention with StripeStarts on a clock · 22 stepsGmailGoogle SheetsPostgresData collectionAIAutomatic service with Gemini and PostgresStarts on another system calling it · 22 stepsPostgresRedisData collectionAIServe a RAG chat backend for Next.js with OpenAI and RedisStarts on another system calling it · 23 stepsPineconePostgresRedisData collectionAITaxi service provider with Grok and PostgresStarts on someone opening a chat with it · 24 stepsPostgresRedisData collectionAIConversing with OpenAI and PostgresStarts on someone opening a chat with it · 25 stepsPostgresData collectionAIThe title is very good, clearly conveying the template's purposeStarts on a clock · 25 stepsGmailPostgresRSSData collectionAIAutomated email responses with OpenAI and SupabaseStarts on an event in a connected app · 27 stepsOutlookPostgresSupabaseSupabase vectorsData collectionAIAI chatbot call center: Taxi service with Grok and PostgresStarts on someone opening a chat with it · 33 stepsPostgresRedisData collectionAICreate a self-updating RAG chatbot with Google DriveStarts on someone opening a chat with it · 34 stepsGoogle DrivePostgresSupabaseSupabase vectorsData collectionAIFrom sitemap crawling to vector storage: Creating an efficientStarts on an event in a connected app · 35 stepsPostgresSupabaseSupabase vectorsData collectionAIFilter URLs with Gemini and GroqStarts on a clock · 37 stepsPostgresData collectionAICentral AI agent of an IT company with Gemini and OpenRouterStarts on someone opening a chat with it · 39 stepsGoogle DrivePineconePostgresData collectionAIInteractive knowledge base chat with Supabase RAGStarts on someone opening a chat with it · 43 stepsGmailGoogle DrivePostgresSupabaseData collectionAIWordPress - AI chatbot to enhance user experienceStarts on someone opening a chat with it · 45 stepsPostgresSupabaseSupabase vectorsWordPressData collectionAIAI personal assistant with RAG and SupabaseStarts on another system calling it · 64 stepsPostgresRedisSupabaseSupabase vectors

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.