Inngest
Durable execution for workflows and AI agents with zero infrastructure overhead.
Inngest stands out for developers who want durable execution without operational overhead. Its code-first approach and new Experiments/Deferred Features make it a strong choice for AI agent workflows, but teams needing strict state machine control may still prefer Temporal.
- AI agent orchestration needing pause/resume for human input
- Multi-tenant SaaS platforms requiring per-user concurrency control
- Background job processing without managing queues or workers
- Reliable event-driven workflows with automatic retries
- Organizations needing fine-grained workflow state machines like Temporal
- Projects requiring strict message ordering and exactly-once guarantees
- Teams that prefer a visual workflow builder over code-first APIs
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Skip Inngest if you need a visual workflow builder with drag-and-drop state machine design, strict message ordering, or a fully self-hosted deployment with no dependency on cloud managed services.
Going past 50k executions on the Hobby plan pauses execution entirely until you upgrade or the next month.
Inngest's Hobby ($0/mo) is great for solo devs and side projects; Pro ($75/mo) fits growing teams needing more concurrency and traces. Enterprise is custom-priced but includes SAML and dedicated support. Compared to Temporal Cloud (starts at $100/mo for similar throughput) or AWS Step Functions (pay per state transition), Inngest's value is strongest at mid-scale.
In short
Inngest — Durable execution for workflows and AI agents with zero infrastructure overhead. Best for AI agent orchestration needing pause/resume for human input, Multi-tenant SaaS platforms requiring per-user concurrency control, Background job processing without managing queues or workers. Free to start; paid plans from $99/mo.
What's new in Inngest
Checked 11 days agoAcross the latest 8 updates: 7 feature updates and 1 changelog entry.
Sessions: investigate related runs
Sessions: group runs by session key for investigating related work like conversations or support tickets.
Scoring: judge how well your AI actually performed
Scoring beta: attach named quality signals to runs or steps via inngest.score(), with deferred LLM-as-judge support.
Experiments: safely test code changes against live production traffic
group.experiment() lets you compare step variants on live traffic with durable memoization per run.
Query your executions: Insights now supports querying runs, steps, and traces
Insights now allows SQL queries over runs, steps, and trace data — no export needed.
Debug functions from the terminal with new CLI commands and v2 REST API
New CLI 'api' subcommands and v2 REST API for inspecting runs/step traces from terminal or CI.
There are too many JavaScript schema libraries, so support only one
Inngest adopts Standard Schema in TypeScript SDK to unify validation across libraries.
Introducing defer(): Giving Follow-Up Work the Context it Never Had
defer() API for launching typed, durable follow-up work from inside a function without blocking.
Inngest, meet your coding agent
Official plugins and skills for Claude Code, Codex, Cursor, and other coding agents.
Viability Score
How likely is Inngest to still be operational in 12 months? Based on 4 signals — momentum (how recently it shipped), wrapper dependency, revenue model, and web presence.
Last calculated: July 2026
How we score →Key Features
- Step-based durable execution with automatic retries
- Wait for events mid-execution to pause agents
- Invoke other functions as steps in a workflow
- Per-tenant concurrency and rate limiting via flow control
- Full trace observability with failure replay
- Fan out thousands of jobs per event
- Serverless functions that persist state across invocations
- Scheduled cron jobs with missed-run recovery
- Long-running API endpoints (Durable Endpoints)
- Deploy to any cloud (serverless, servers, etc.)
- Local development in one command
- Deferred Functions for fire-and-forget background work
- Experiments for A/B testing step variants in production
- Insights with SQL querying over runs, steps, traces
- Scoring and Sessions for attaching quality signals
About Inngest
Inngest is a developer platform that brings durability directly into your codebase, enabling unbreakable workflows, AI agents, and background jobs without managing queues or workers. By wrapping existing code with step.run(), each function call automatically persists state, retries on failure, and survives server restarts. Designed for engineers who want to focus on business logic, Inngest supports serverless functions, scheduled tasks, long-running endpoints, and event-driven fan-out. Key features include step-based durable execution with automatic retries, wait-for-event to pause agents mid-execution for human input, per-tenant concurrency and rate limiting via flow control, and full trace observability with failure replay. Recent additions like Experiments for A/B testing step variants in production, Deferred Functions for fire-and-forget background work, and Insights with SQL querying over runs, steps, and traces further extend its capabilities. Inngest also integrates with Claude Code, Cursor, Codex, Vercel, Netlify, Cloudflare Pages, and more. Pricing starts at a free Hobby tier (50k executions/month) and Pro at $99/mo for 1M+ executions. Enterprise plans offer custom scale, SAML, and dedicated support. Unlike traditional queues or Temporal, Inngest requires no separate infrastructure—durability lives in your code, making it ideal for AI agent orchestration, multi-tenant SaaS, and background job processing.
Behind the Verdict
Inngest solves a real pain: building reliable workflows without babysitting queues. The step.run() pattern is dead simple—wrap your code and get retries, state persistence, and observability for free. For AI agents that need to pause for human input or wait on external events, step.waitForEvent() is a killer feature. Where it shines is multi-tenant scenarios. Per-tenant concurrency and rate limiting are built-in with one line of code, so one noisy tenant can't starve others. The new Experiments feature lets you safely A/B test step variants in production, judged on real outcomes—great for iterative agent development. When to pass: if you need exactly-once semantics and strict ordering, Inngest's at-least-once model may not suffice. For complex state machines with many branching paths, Temporal offers more explicit control. Also, self-hosting the cloud features requires additional setup. Compared to Temporal, Inngest wins on developer experience (no separate service to run, code-native) but loses on raw flexibility. For most teams building AI agents or background jobs, Inngest is the pragmatic choice.
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Real-world workflow fit
Concrete scenarios for the personas Inngest actually fits — and what changes day-one when you adopt it.
You need an agent that pauses to wait for human approval before executing an action, retries on LLM failure, and logs all steps.
Outcome: With Inngest, you define a function with step.run() and step.waitForEvent(); the agent pauses mid-execution, resumes on approval, and automatically retries failed steps without starting over.
You run a nightly sync that must not exceed API rate limits and needs to recover missed runs if the service restarts.
Outcome: Schedule a cron job in Inngest with per-tenant concurrency; missed runs recover automatically, and each batch respects the rate limit. Observability shows every execution.
Use Cases
- Build a durable AI agent that retries LLM calls on failure and persists state across multi-step reasoning.
- Automate lead enrichment by fanning out parallel scrapes and LLM scoring, then writing results to CRM.
- Create a real-time collaborative feature by publishing events on user actions and subscribing to updates.
- Implement a user-defined workflow engine where customers chain custom steps with retry and rollback.
- Run a scheduled cron job that processes batches with concurrency controls to avoid API rate limits.
- Orchestrate a multi-step email sequence triggered by user behavior, with throttling per segment.
- Build a durable API endpoint with Durable Endpoints for automatic retries and observability.
- Defer follow-up work (scoring, notifications) using Deferred Functions for independent background runs.
Limitations
- Inngest is an event-driven durable execution platform, not an AI model provider.
- It focuses on workflow orchestration for AI agents and serverless functions.
- Limitations depend on pricing plan: Hobby plan caps at 50k executions/month and 5 concurrent steps; Pro increases to 1M executions and 100 concurrent steps.
- Enterprise offers custom limits.
- The open-source core lacks managed observability and scalability features.
as of 2026-06-30
12-month cost
Project the real annual outlay, including the implied monthly cost when only an annual tier is published.
Vendor list price only. Add-on usage, seat overages, and contract minimums are surfaced under Hidden costs & gotchas.
Plans compared
For each published Inngest tier: who it actually fits, and what it adds vs. the previous tier. Cross-reference the cost calculator above for projected annual outlay.
Hobby
$0/mo
Ideal for
Individual developers and small projects exploring durable execution with low throughput (under 50k runs/mo).
What this tier adds
Free entry point with 5 concurrent steps, 50k executions/mo, 500k events, 24-hour trace retention.
Pro
$99/mo
Ideal for
Growing teams building production workflows needing higher concurrency (100 steps) and 7-day trace retention.
What this tier adds
Adds 100+ concurrent steps, 1M+ executions/mo, 7-day trace retention, metered overage billing.
Enterprise
Contact us
Ideal for
Organizations running critical workflows at scale requiring custom limits, SAML, RBAC, and dedicated support.
What this tier adds
Custom executions, 90-day trace retention, SSO/SAML/RBAC, dedicated Slack channel, HIPAA BAA.
Where the pricing makes sense
The company stage and team size where Inngest's pricing actually pencils out — and where peers do it cheaper.
Inngest's Hobby ($0/mo) is great for solo devs and side projects; Pro ($75/mo) fits growing teams needing more concurrency and traces. Enterprise is custom-priced but includes SAML and dedicated support. Compared to Temporal Cloud (starts at $100/mo for similar throughput) or AWS Step Functions (pay per state transition), Inngest's value is strongest at mid-scale.
Setup time & first value
How long it actually takes to get something useful out of Inngest — broken out by persona, not the marketing-page minute.
For an individual developer: install the SDK (npm install inngest), run npx inngest-cli dev, and define your first function in under 10 minutes. Teams with existing Node.js/TypeScript codebases can integrate within 30 minutes. Python and Go users need to set up the SDK and sync their app, typically under 1 hour.
Switching to or from Inngest
How to bring data in from common predecessors and how to get it back out — written for the switcher, not the buyer.
- →From Bull/Redis queues: replace job handlers with Inngest functions; events replace queue push. No major code change needed.
- →From AWS SQS + Lambda: move event handling to Inngest; batch and retry logic simplifies.
- →From Sidekiq: rewrite worker jobs as Inngest steps; use step.run() for each retryable unit.
- →From Temporal: Inngest offers a simpler API but less state machine control; migrate step logic to step.run() callbacks.
- →From Zapier/Workato: Inngest is code-first; you'll need to write event handlers and steps rather than use visual flows.
- ↗To Temporal: export run history via Inngest's trace export to analyze workflow shape, then re-implement state machines manually.
- ↗To AWS Step Functions: rewrite each Inngest step as a Step Functions state; note that Step Functions charges per state transition and has no built-in event wait.
- ↗To custom queue + worker: extract event handlers and retry logic into your own infrastructure; you'll need to implement observability, flow control, and replay from scratch.
Integrations
Resources & Guides
Official links
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Common stack mates teams adopt alongside Inngest, with the specific reason each pairing earns its keep.
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