Inngest

Inngest is an event-driven workflow platform that provides a powerful execution engine for AI agent pipelines. It enables developers to build complex, multi-step agent workflows as durable functions with automatic retries, event triggers, and built-in AI middleware for common LLM operations.

The platform's core abstraction is the step function — a workflow defined as a series of steps that execute reliably with built-in state management. Each step is individually retryable, meaning if step 4 of a 10-step agent workflow fails, only step 4 retries — not the entire workflow. This dramatically improves reliability and cost efficiency for LLM-heavy pipelines.

Inngest's AI middleware layer (called AgentKit) provides built-in support for common agent patterns: LLM calls with automatic retry on rate limits, tool execution with validation, agent routing, and multi-agent orchestration. AgentKit handles the boilerplate of building reliable agent systems while giving developers full control over agent logic.

The event-driven architecture means agent workflows can be triggered by any event — webhooks, scheduled cron jobs, other workflow completions, or custom application events. Events carry data payloads that are automatically available to workflow steps, enabling reactive agent systems that respond to real-world triggers.

Inngest supports TypeScript and Python SDKs, making it accessible to agent developers in both ecosystems. Workflows can fan out into parallel branches, wait for external events (human-in-the-loop approval, webhook callbacks), and implement complex conditional logic.

The platform includes built-in observability with execution traces, step-level timing, and failure analysis. A visual flow editor shows workflow structure and execution state, making it easy to understand and debug complex agent pipelines.

Inngest can be used as a cloud service or self-hosted. The cloud version includes a generous free tier with automatic scaling. Self-hosting via Docker gives full data control for enterprise deployments.

For teams building production agent systems that need reliability beyond what simple async/await provides, Inngest offers a compelling solution. Its step-level durability, event-driven triggers, and AI middleware make it particularly well-suited for the unpredictable, long-running, failure-prone nature of AI agent workloads.