Added use cases section in the docs (#2641)
* Started adding use cases pages * Updates * More improvements * Improved diagrams * Added overview page * More copy + diagram updates * Improved diagram titles * Further diagram improvements * Corrected workflow * Updated copy * Typos * Updated intro file * Reverted aiRunFilterService.server.ts
This commit is contained in:
@@ -333,6 +333,16 @@
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}
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]
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},
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{
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"group": "Use cases",
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"pages": [
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"guides/use-cases/overview",
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"guides/use-cases/data-processing-etl",
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"guides/use-cases/media-generation",
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"guides/use-cases/media-processing",
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"guides/use-cases/marketing"
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]
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},
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{
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"group": "Example projects",
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"pages": [
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@@ -15,6 +15,8 @@ mode: "center"
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<Card title="SvelteKit" img="/images/logo-svelte.png" href="/guides/community/sveltekit" />
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</CardGroup>
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import UseCasesCards from "/snippets/use-cases-cards.mdx";
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## Guides
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Get set up fast using our detailed walk-through guides.
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@@ -39,6 +41,8 @@ Get set up fast using our detailed walk-through guides.
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| [Using webhooks in Next.js](/guides/frameworks/nextjs-webhooks) | Trigger tasks from a webhook in Next.js |
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| [Using webhooks in Remix](/guides/frameworks/remix-webhooks) | Trigger tasks from a webhook in Remix |
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<UseCasesCards />
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## Example projects
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Example projects are full projects with example repos you can fork and use. These are a great way of learning how to use Trigger.dev in your projects.
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@@ -0,0 +1,159 @@
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---
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title: "Data processing & ETL workflows"
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sidebarTitle: "Data processing & ETL"
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description: "Learn how to use Trigger.dev for data processing and ETL (Extract, Transform, Load), including web scraping, database synchronization, batch enrichment and more."
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---
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import UseCasesCards from "/snippets/use-cases-cards.mdx";
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## Overview
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Build complex data pipelines that process large datasets without timeouts. Handle streaming analytics, batch enrichment, web scraping, database sync, and file processing with automatic retries and progress tracking.
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## Featured examples
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<CardGroup cols={3}>
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<Card
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title="Realtime CSV importer"
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icon="book"
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href="/guides/example-projects/realtime-csv-importer"
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>
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Import CSV files with progress streamed live to frontend.
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</Card>
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<Card title="Web scraper with BrowserBase" icon="book" href="/guides/examples/scrape-hacker-news">
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Scrape websites using BrowserBase and Puppeteer.
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</Card>
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<Card
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title="Supabase database webhooks"
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icon="book"
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href="/guides/frameworks/supabase-edge-functions-database-webhooks"
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>
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Trigger tasks from Supabase database webhooks.
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</Card>
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</CardGroup>
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## Benefits of using Trigger.dev for data processing & ETL workflows
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**Process datasets for hours without timeouts:** Handle multi-hour transformations, large file processing, or complete database exports. No execution time limits.
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**Parallel processing with built-in rate limiting:** Process thousands of records simultaneously while respecting API rate limits. Scale efficiently without overwhelming downstream services.
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**Stream progress to your users in real-time:** Show row-by-row processing status updating live in your dashboard. Users see exactly where processing is and how long remains.
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## Production use cases
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<CardGroup cols={1}>
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<Card title="MagicSchool AI customer story" href="https://trigger.dev/customers/magicschool-ai-customer-story">
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Read how MagicSchool AI uses Trigger.dev to generate insights from millions of student interactions.
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</Card>
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<Card title="Comp AI customer story" href="https://trigger.dev/customers/comp-ai-customer-story">
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Read how Comp AI uses Trigger.dev to automate evidence collection at scale, powering their open source, AI-driven compliance platform.
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</Card>
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<Card title="Midday customer story" href="https://trigger.dev/customers/midday-customer-story">
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Read how Midday use Trigger.dev to sync large volumes of bank transactions in their financial management platform.
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</Card>
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</CardGroup>
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## Example workflow patterns
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<Tabs>
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<Tab title="CSV file import">
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Simple CSV import pipeline. Receives file upload, parses CSV rows, validates data, imports to database with progress tracking.
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<div align="center">
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```mermaid
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graph TB
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A[importCSV] --> B[parseCSVFile]
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B --> C[validateRows]
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C --> D[bulkInsertToDB]
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D --> E[notifyCompletion]
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```
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</div>
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</Tab>
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<Tab title="Multi-source ETL pipeline">
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**Coordinator pattern with parallel extraction**. Batch triggers parallel extraction from multiple sources (APIs, databases, S3), transforms and validates data, loads to data warehouse with monitoring.
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<div align="center">
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```mermaid
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graph TB
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A[runETLPipeline] --> B[coordinateExtraction]
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B --> C[batchTriggerAndWait]
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C --> D[extractFromAPI]
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C --> E[extractFromDatabase]
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C --> F[extractFromS3]
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D --> G[transformData]
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E --> G
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F --> G
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G --> H[validateData]
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H --> I[loadToWarehouse]
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```
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</div>
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</Tab>
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<Tab title="Parallel web scraping">
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**Coordinator pattern with browser automation**. Launches headless browsers in parallel to scrape multiple pages, extracts structured data, cleans and normalizes content, stores in database.
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<div align="center">
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```mermaid
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graph TB
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A[scrapeSite] --> B[coordinateScraping]
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B --> C[batchTriggerAndWait]
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C --> D[scrapePage1]
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C --> E[scrapePage2]
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C --> F[scrapePageN]
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D --> G[cleanData]
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E --> G
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F --> G
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G --> H[normalizeData]
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H --> I[storeInDatabase]
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```
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</div>
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</Tab>
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<Tab title="Batch data enrichment">
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**Coordinator pattern with rate limiting**. Fetches records needing enrichment, batch triggers parallel API calls with configurable concurrency to respect rate limits, validates enriched data, updates database.
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<div align="center">
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```mermaid
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graph TB
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A[enrichRecords] --> B[fetchRecordsToEnrich]
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B --> C[coordinateEnrichment]
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C --> D[batchTriggerAndWait]
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D --> E[enrichRecord1]
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D --> F[enrichRecord2]
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D --> G[enrichRecordN]
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E --> H[validateEnrichedData]
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F --> H
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G --> H
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H --> I[updateDatabase]
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```
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</div>
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</Tab>
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</Tabs>
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<UseCasesCards />
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@@ -0,0 +1,147 @@
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---
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title: "Marketing workflows"
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sidebarTitle: "Marketing"
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description: "Learn how to use Trigger.dev for marketing workflows, including drip campaigns, behavioral triggers, personalization engines, and AI-powered content workflows"
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---
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import UseCasesCards from "/snippets/use-cases-cards.mdx";
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## Overview
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Build marketing workflows from email drip sequences to orchestrating full multi-channel campaigns. Handle multi-day sequences, behavioral triggers, dynamic content generation, and build live analytics dashboards.
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## Featured examples
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<CardGroup cols={3}>
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<Card
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title="Email sequences with Resend"
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icon="book"
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href="/guides/examples/resend-email-sequence"
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>
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Send multi-day email sequences with wait delays between messages.
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</Card>
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<Card
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title="Product image generator"
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icon="book"
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href="/guides/example-projects/product-image-generator"
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>
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Transform product photos into professional marketing images using Replicate.
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</Card>
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<Card
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title="Human-in-the-loop workflow"
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icon="book"
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href="/guides/example-projects/human-in-the-loop-workflow"
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>
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Approve marketing content using a human-in-the-loop workflow.
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</Card>
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</CardGroup>
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## Benefits of using Trigger.dev for marketing workflows
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**Delays without idle costs:** Wait hours or weeks between steps. Waits over 5 seconds are automatically checkpointed and don't count towards compute usage. Perfect for drip campaigns and scheduled follow-ups.
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**Guaranteed delivery:** Messages send exactly once, even after retries. Personalized content isn't regenerated on failure.
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**Scale without limits:** Process thousands in parallel while respecting rate limits. Send to entire segments without overwhelming APIs.
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## Production use cases
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||||
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<Card title="Icon customer story" href="https://trigger.dev/customers/icon-customer-story">
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||||
|
||||
Read how Icon uses Trigger.dev to process and generate thousands of videos per month for their AI-driven video creation platform.
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</Card>
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## Example workflow patterns
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<Tabs>
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<Tab title="Drip email campaign">
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Simple drip campaign. User signs up, waits specified delay, sends personalized email, tracks engagement.
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<div align="center">
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```mermaid
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graph TB
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A[userCreateAccount] --> B[sendWelcomeEmail]
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B --> C[wait.for 24h]
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C --> D[sendProductTipsEmail]
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D --> E[wait.for 7d]
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E --> F[sendFeedbackEmail]
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```
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</div>
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</Tab>
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<Tab title="Multi-channel campaigns">
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**Router pattern with delay orchestration**. User action triggers campaign, router selects channel based on preferences (email/SMS/push), coordinates multi-day sequence with delays between messages, tracks engagement across channels.
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<div align="center">
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```mermaid
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graph TB
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A[startCampaign] --> B[fetchUserProfile]
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B --> C[selectChannel]
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C --> D{Preferred<br/>Channel?}
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D -->|Email| E[sendEmail1]
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D -->|SMS| F[sendSMS1]
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D -->|Push| G[sendPush1]
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E --> H[wait.for 2d]
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F --> H
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G --> H
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H --> I[sendFollowUp]
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I --> J[trackConversion]
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```
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</div>
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</Tab>
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<Tab title="AI content with approval">
|
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**Supervisor pattern with approval gate**. Generates AI marketing content (images, copy, assets), pauses with wait.forToken for human review, applies revisions if needed, publishes to channels after approval.
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<div align="center">
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```mermaid
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graph TB
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A[createCampaignAssets] --> B[generateAIContent]
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B --> C[wait.forToken approval]
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C --> D{Approved?}
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D -->|Yes| E[publishToChannels]
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D -->|Needs revision| F[applyFeedback]
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F --> B
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```
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</div>
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</Tab>
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<Tab title="Survey response enrichment">
|
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**Coordinator pattern with enrichment**. User completes survey, batch triggers parallel enrichment from CRM/analytics, analyzes and scores responses, updates customer profiles, triggers personalized follow-up campaigns.
|
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<div align="center">
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```mermaid
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graph TB
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A[processSurveyResponse] --> B[coordinateEnrichment]
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B --> C[batchTriggerAndWait]
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C --> D[fetchCRMData]
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C --> E[fetchAnalytics]
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C --> F[fetchBehaviorData]
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D --> G[analyzeAndScore]
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E --> G
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F --> G
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||||
|
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G --> H[updateCRMProfile]
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H --> I[triggerFollowUp]
|
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```
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|
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</div>
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</Tab>
|
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</Tabs>
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<UseCasesCards />
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@@ -0,0 +1,144 @@
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---
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title: "AI media generation workflows"
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sidebarTitle: "AI media generation"
|
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description: "Learn how to use Trigger.dev for AI media generation including image creation, video synthesis, audio generation, and multi-modal content workflows"
|
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---
|
||||
|
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import UseCasesCards from "/snippets/use-cases-cards.mdx";
|
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|
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## Overview
|
||||
|
||||
Build AI media generation pipelines that handle unpredictable API latencies and long-running operations. Generate images, videos, audio, and multi-modal content with automatic retries, progress tracking, and no timeout limits.
|
||||
|
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## Featured examples
|
||||
|
||||
<CardGroup cols={3}>
|
||||
<Card
|
||||
title="Product image generator"
|
||||
icon="book"
|
||||
href="/guides/example-projects/product-image-generator"
|
||||
>
|
||||
Transform product photos into professional marketing images using Replicate.
|
||||
</Card>
|
||||
<Card
|
||||
title="Meme generator (human-in-the-loop)"
|
||||
icon="book"
|
||||
href="/guides/example-projects/meme-generator-human-in-the-loop"
|
||||
>
|
||||
Generate memes with DALL·E 3 and add human approval steps.
|
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</Card>
|
||||
<Card
|
||||
title="Vercel AI SDK image generation"
|
||||
icon="book"
|
||||
href="/guides/example-projects/vercel-ai-sdk-image-generator"
|
||||
>
|
||||
Generate images from text prompts using the Vercel AI SDK.
|
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</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Benefits of using Trigger.dev for AI media generation workflows
|
||||
|
||||
**Pay only for active compute, not AI inference time:** Checkpoint-resume pauses during AI API calls. Generate content that takes minutes or hours without paying for idle inference time.
|
||||
|
||||
**No timeout limits for long generations:** Handle generations that take minutes or hours without execution limits. Perfect for high-quality video synthesis and complex multi-modal workflows.
|
||||
|
||||
**Human approval gates for brand safety:** Add review steps before publishing AI-generated content. Pause workflows for human approval using waitpoint tokens.
|
||||
|
||||
## Production use cases
|
||||
|
||||
<CardGroup cols={1}>
|
||||
|
||||
<Card title="Icon customer story" href="https://trigger.dev/customers/icon-customer-story">
|
||||
|
||||
Read how Icon uses Trigger.dev to process and generate thousands of videos per month for their AI-driven video creation platform.
|
||||
|
||||
</Card>
|
||||
|
||||
<Card title="Papermark customer story" href="https://trigger.dev/customers/papermark-customer-story">
|
||||
|
||||
Read how Papermark process thousands of documents per month using Trigger.dev.
|
||||
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Example workflow patterns
|
||||
|
||||
<Tabs>
|
||||
<Tab title="AI content with approval">
|
||||
**Supervisor pattern with approval gate**. Generates AI content, pauses execution with wait.forToken to allow human review, applies feedback if needed, publishes approved content.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[generateContent] --> B[createWithAI]
|
||||
B --> C[wait.forToken approval]
|
||||
C --> D{Approved?}
|
||||
|
||||
D -->|Yes| E[publishContent]
|
||||
D -->|Needs revision| F[applyFeedback]
|
||||
F --> B
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
<Tab title="AI image generation">
|
||||
Simple AI image generation. Receives prompt and parameters, calls OpenAI DALL·E 3, post-processes result, uploads to storage.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[generateImage] --> B[optimizeImage]
|
||||
B --> C[uploadToStorage]
|
||||
C --> D[updateDatabase]
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
<Tab title="Batch image generation">
|
||||
**Coordinator pattern with rate limiting**. Receives batch of generation requests, coordinates parallel processing with configurable concurrency to respect API rate limits, validates outputs, stores results.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processBatch] --> B[coordinateGeneration]
|
||||
B --> C[batchTriggerAndWait]
|
||||
|
||||
C --> D[generateImage1]
|
||||
C --> E[generateImage2]
|
||||
C --> F[generateImageN]
|
||||
|
||||
D --> G[validateResults]
|
||||
E --> G
|
||||
F --> G
|
||||
|
||||
G --> H[storeResults]
|
||||
H --> I[notifyCompletion]
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
<Tab title="Multi-step image enhancement">
|
||||
**Coordinator pattern with sequential processing**. Generates initial content with AI, applies style transfer or enhancement, upscales resolution, optimizes and compresses for delivery.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processCreative] --> B[generateWithAI]
|
||||
B --> C[applyStyleTransfer]
|
||||
C --> D[upscaleResolution]
|
||||
D --> E[optimizeAndCompress]
|
||||
E --> F[uploadToStorage]
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
</Tabs>
|
||||
|
||||
<UseCasesCards />
|
||||
@@ -0,0 +1,191 @@
|
||||
---
|
||||
title: "Media processing workflows"
|
||||
sidebarTitle: "Media processing"
|
||||
description: "Learn how to use Trigger.dev for media processing including video transcoding, image optimization, audio transformation, and document conversion."
|
||||
---
|
||||
|
||||
import UseCasesCards from "/snippets/use-cases-cards.mdx";
|
||||
|
||||
## Overview
|
||||
|
||||
Build media processing pipelines that handle large files and long-running operations. Process videos, images, audio, and documents with automatic retries, progress tracking, and no timeout limits.
|
||||
|
||||
## Featured examples
|
||||
|
||||
<CardGroup cols={3}>
|
||||
<Card title="FFmpeg video processing" icon="book" href="/guides/examples/ffmpeg-video-processing">
|
||||
Process videos and upload results to R2 storage using FFmpeg.
|
||||
</Card>
|
||||
<Card
|
||||
title="Product image generator"
|
||||
icon="book"
|
||||
href="/guides/example-projects/product-image-generator"
|
||||
>
|
||||
Transform product photos into professional marketing images using Replicate.
|
||||
</Card>
|
||||
<Card
|
||||
title="LibreOffice PDF conversion"
|
||||
icon="book"
|
||||
href="/guides/examples/libreoffice-pdf-conversion"
|
||||
>
|
||||
Convert documents to PDF using LibreOffice.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
|
||||
## Benefits of using Trigger.dev for media processing workflows
|
||||
|
||||
**Process multi-hour videos without timeouts:** Transcode videos, extract frames, or run CPU-intensive operations for hours. No execution time limits.
|
||||
|
||||
**Stream progress to users in real-time:** Show processing status updating live in your UI. Users see exactly where encoding is and how long remains.
|
||||
|
||||
**Parallel processing with resource control:** Process hundreds of files simultaneously with configurable concurrency limits. Control resource usage without overwhelming infrastructure.
|
||||
|
||||
## Example workflow patterns
|
||||
|
||||
<Tabs>
|
||||
<Tab title="Video transcode">
|
||||
Simple video transcoding pipeline. Downloads video from storage, batch triggers parallel transcoding to multiple formats and thumbnail extraction, uploads all results.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processVideo] --> B[downloadFromStorage]
|
||||
B --> C[batchTriggerAndWait]
|
||||
|
||||
C --> D[transcodeToHD]
|
||||
C --> E[transcodeToSD]
|
||||
C --> F[extractThumbnail]
|
||||
|
||||
D --> G[uploadToStorage]
|
||||
E --> G
|
||||
F --> G
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
<Tab title="Adaptive video processing">
|
||||
**Router + Coordinator pattern**. Analyzes video metadata to determine source resolution, routes to appropriate transcoding preset, batch triggers parallel post-processing for thumbnails, preview clips, and chapter detection.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processVideoUpload] --> B[analyzeMetadata]
|
||||
B --> C{Source<br/>Resolution?}
|
||||
|
||||
C -->|4K Source| D[transcode4K]
|
||||
C -->|HD Source| E[transcodeHD]
|
||||
C -->|SD Source| F[transcodeSD]
|
||||
|
||||
D --> G[coordinatePostProcessing]
|
||||
E --> G
|
||||
F --> G
|
||||
|
||||
G --> H[batchTriggerAndWait]
|
||||
H --> I[extractThumbnails]
|
||||
H --> J[generatePreview]
|
||||
H --> K[detectChapters]
|
||||
|
||||
I --> L[uploadToStorage]
|
||||
J --> L
|
||||
K --> L
|
||||
|
||||
L --> M[notifyComplete]
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
<Tab title="Smart image optimization">
|
||||
**Router + Coordinator pattern**. Analyzes image content to detect type, routes to specialized processing (background removal for products, face detection for portraits, scene analysis for landscapes), upscales with AI, batch triggers parallel variant generation.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processImageUpload] --> B[analyzeContent]
|
||||
B --> C{Content<br/>Type?}
|
||||
|
||||
C -->|Product| D[removeBackground]
|
||||
C -->|Portrait| E[detectFaces]
|
||||
C -->|Landscape| F[analyzeScene]
|
||||
|
||||
D --> G[upscaleWithAI]
|
||||
E --> G
|
||||
F --> G
|
||||
|
||||
G --> H[batchTriggerAndWait]
|
||||
H --> I[generateWebP]
|
||||
H --> J[generateThumbnails]
|
||||
H --> K[generateSocialCrops]
|
||||
|
||||
I --> L[uploadToStorage]
|
||||
J --> L
|
||||
K --> L
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
<Tab title="Podcast production">
|
||||
**Coordinator pattern**. Pre-processes raw audio with noise reduction and speaker diarization, batch triggers parallel tasks for transcription (Deepgram), audio enhancement, and chapter detection, aggregates results to generate show notes and publish.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processAudioUpload] --> B[cleanAudio]
|
||||
B --> C[coordinateProcessing]
|
||||
|
||||
C --> D[batchTriggerAndWait]
|
||||
D --> E[transcribeWithDeepgram]
|
||||
D --> F[enhanceAudio]
|
||||
D --> G[detectChapters]
|
||||
|
||||
E --> H[generateShowNotes]
|
||||
F --> H
|
||||
G --> H
|
||||
|
||||
H --> I[publishToPlatforms]
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
|
||||
<Tab title="Document extraction with approval">
|
||||
**Router pattern with human-in-the-loop**. Detects file type and routes to appropriate processor, classifies document with AI to determine type (invoice/contract/receipt), extracts structured data fields, optionally pauses with wait.forToken for human approval.
|
||||
|
||||
<div align="center">
|
||||
|
||||
```mermaid
|
||||
graph TB
|
||||
A[processDocumentUpload] --> B[detectFileType]
|
||||
|
||||
B -->|PDF| C[extractText]
|
||||
B -->|Word/Excel| D[convertToPDF]
|
||||
B -->|Image| E[runOCR]
|
||||
|
||||
C --> F[classifyDocument]
|
||||
D --> F
|
||||
E --> F
|
||||
|
||||
F -->|Invoice| G[extractLineItems]
|
||||
F -->|Contract| H[extractClauses]
|
||||
F -->|Receipt| I[extractExpenses]
|
||||
|
||||
G --> J{Needs<br/>Review?}
|
||||
H --> J
|
||||
I --> J
|
||||
|
||||
J -->|Yes| K[wait.forToken approval]
|
||||
J -->|No| L[processAndIntegrate]
|
||||
K --> L
|
||||
```
|
||||
|
||||
</div>
|
||||
</Tab>
|
||||
</Tabs>
|
||||
|
||||
<UseCasesCards />
|
||||
@@ -0,0 +1,11 @@
|
||||
---
|
||||
title: "Use cases"
|
||||
sidebarTitle: "Overview"
|
||||
description: "Explore common use cases for Trigger.dev including data processing, media workflows, marketing automation, and AI generation"
|
||||
---
|
||||
|
||||
import UseCasesCards from "/snippets/use-cases-cards.mdx";
|
||||
|
||||
Trigger.dev handles workflows that traditional platforms struggle with: long-running operations, unpredictable API latencies, multi-hour processing, and complex orchestration patterns. Our platform provides no timeout limits, automatic retries, and real-time progress tracking built in.
|
||||
|
||||
<UseCasesCards />
|
||||
@@ -0,0 +1,24 @@
|
||||
## Featured use cases
|
||||
|
||||
<CardGroup cols={2}>
|
||||
<Card
|
||||
title="Data processing & ETL workflows"
|
||||
icon="database"
|
||||
href="/guides/use-cases/data-processing-etl"
|
||||
>
|
||||
Build complex data pipelines that process large datasets without timeouts.
|
||||
</Card>
|
||||
<Card title="Media processing workflows" icon="film" href="/guides/use-cases/media-processing">
|
||||
Batch process videos, images, audio, and documents with no execution time limits.
|
||||
</Card>
|
||||
<Card
|
||||
title="AI media generation workflows"
|
||||
icon="wand-magic-sparkles"
|
||||
href="/guides/use-cases/media-generation"
|
||||
>
|
||||
Generate images, videos, audio, documents and other media using AI models.
|
||||
</Card>
|
||||
<Card title="Marketing workflows" icon="bullhorn" href="/guides/use-cases/marketing">
|
||||
Build drip campaigns, create marketing content, and orchestrate multi-channel campaigns.
|
||||
</Card>
|
||||
</CardGroup>
|
||||
Reference in New Issue
Block a user