Problem

Trigger.dev addresses the gap between easy AI prototypes and reliable production-grade asynchronous work. Modern product teams need jobs that run beyond request timeouts—AI agents, media processing, data pipelines, browser automation, scheduled tasks, and human-in-the-loop workflows—but implementing queues, retries, state management, concurrency, observability, and elastic scaling inside an application is costly and failure-prone. The pain is especially acute for long, multi-step, compute-variable workflows: when a late step fails, rebuilding the surrounding infrastructure or repeating completed work wastes engineering time and compute.

The main use case is production AI-agent and background-job execution that must survive failures and scale with demand. Trigger.dev’s customer examples include thousands of custom LLM workflows, WhatsApp messaging, ETL synchronization, and durable asynchronous tasks; its own positioning emphasizes that prototyping AI is easy, while building reliable production agents is not.

Product / Service

Trigger.dev is a code-first managed compute platform for building AI agents and workflows in TypeScript. Developers define tasks as normal TypeScript functions in their codebase, deploy them as a bundled application to Trigger.dev’s managed infrastructure, and can alternatively self-host the platform. The service provides queues, elastic infrastructure, scheduling, concurrency controls, automatic retries, checkpointing, logging, tracing, dashboards, and real-time monitoring without requiring teams to provision or scale worker infrastructure themselves.

Its durability model combines checkpoint-resume execution with idempotency and cached subtask results, so a failed workflow can retry the failed portion rather than unnecessarily repeating completed work. Trigger.dev charges for compute seconds and task runs; long waits and checkpointed parent tasks do not consume compute while they are paused. That model is designed to fit long-running workloads such as AI summarization, video or media processing, and data pipelines, where execution time varies and infrastructure would otherwise be difficult to manage economically.

Market

Trigger.dev competes in developer infrastructure for background jobs, durable execution, workflow orchestration, and AI-agent runtimes. Its closest alternatives include Temporal and Inngest, while n8n represents a more visual automation approach and BullMQ and QStash are other background-job or queue alternatives. Trigger.dev differentiates itself as a TypeScript-first managed compute platform: tasks remain versioned and tested as application code, execution has no stated timeout or determinism constraints, and the cloud offering manages the workers and scaling. Temporal, by contrast, requires self-managed workers and deterministic workflow constraints, while n8n centers on visual workflow graphs.

The company is well beyond an unvalidated or pre-traction stage. It announced a $3 million seed round in 2023 and a $16 million Series A led by Standard Capital in December 2025. The company reported more than 30,000 developers and hundreds of millions of agent executions per month, with customers or examples including MagicSchool, Icon.com, DavidAI, Cal.com, Magic Patterns, and Algora. The gathered evidence does not disclose revenue, so its precise revenue status cannot be determined; it does, however, show substantial developer adoption, production usage, and institutional funding.