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INNGEST
Durable event-driven workflows for AI apps
MIT
ABOUT
AI applications need reliable, stateful background execution for multi-step agent workflows, async data processing, and scheduled tasks — but building this infrastructure from scratch is complex. Inngest solves this by providing a production-grade platform for durable, event-driven functions that handle retries, failures, observability, and parallelism out of the box. Developers write functions in their existing codebase and Inngest handles the infrastructure: event ingestion, queue management, retry logic, and monitoring — making it natural to build reliable AI agent workflows that can pause, resume, and fan out without custom infrastructure.
INSTALL
npm install inngestINTEGRATION GUIDE
1. Build durable AI agent workflows with multi-step execution, retries, and failure recovery
2. Trigger async data processing when new data arrives via events, webhooks, or scheduled cron jobs
3. Create fan-out patterns where a single event triggers parallel AI processing across multiple functions
4. Build event-driven pipelines that ingest, process, and store AI model outputs with guaranteed delivery
5. Schedule periodic AI tasks — daily reports, model inference, data enrichment — with built-in retry logic
TAGS
workflow-orchestrationevent-drivenbackground-jobsserverlesstypescriptpythonopen-source