About
Hatchet is a developer platform for engineering teams building and deploying AI agents, durable workflows, and background tasks. It serves organizations including financial institutions and corporations, differentiating through durable execution, observability, parallelization, and a fully MIT-licensed, self-hostable platform alongside managed cloud service.
Market
Hatchet competes in developer infrastructure for workflow orchestration, durable execution, background jobs, and AI-agent infrastructure. It positions itself between basic task queues and heavyweight distributed workflow platforms: teams get durable, observable, code-defined workflows with retries, replay, concurrency and fairness controls, while retaining a relatively simple PostgreSQL-centered architecture. Its differentiation is the combination of open-source/self-hosted and managed Cloud offerings, native polyglot SDKs, long-running workers, and built-in operational visibility for complex AI and mission-critical workloads.
Hatchet primarily targets engineering and platform teams at AI startups, scale-ups, and enterprises building AI agents, high-volume background processing, multi-tenant applications, or other mission-critical workflows. The core buyer is a technical leader or developer team that needs durable execution, observability, concurrency controls, and polyglot worker support without operating a more complex distributed workflow system.
At a Glance
Problem
Modern applications increasingly depend on long-running, failure-prone background work: AI agents, document and data pipelines, scheduled jobs, and multi-tenant task queues. Engineering teams often end up stitching together cron systems, queues, retries, concurrency controls, monitoring, and recovery logic themselves. The result is unreliable execution, difficult debugging, wasted compute, and infrastructure that becomes especially expensive when workloads must scale in parallel or run for minutes at a time.
Hatchet’s clearest use case is production AI and document-processing workflows where a failed task can force costly reprocessing or delay customer deliverables. Its customer examples illustrate the payoff: Aevy reports processing 50,000 documents in under an hour instead of nearly a week, while Greptile reports a 50% reduction in failed runs. Hatchet is therefore aimed at converting fragile, bespoke orchestration into a durable execution layer that improves throughput, reliability, and engineering productivity.
Product / Service
Hatchet is an orchestration platform combining a durable task queue, workflow engine, monitoring interface, API, and developer SDKs. Developers define tasks and workflows in Python, TypeScript, Go, or Ruby; Hatchet persists task and agent state, coordinates dependencies, applies retries and timeouts, schedules work, manages fairness and concurrency, and supports replay, streaming, logging, alerting, and observability. Because execution is durably recorded, long-running agents and mission-critical workflows can recover from failures rather than restarting from scratch.
The delivery model separates customer workloads from the orchestration control plane. Workers run on the customer’s infrastructure, while the Hatchet engine is available through Hatchet Cloud or as a self-hosted, MIT-licensed open-source deployment on container platforms such as Kubernetes and Docker. The commercial cloud offering lets teams start without operating the control plane, while self-hosting provides greater control; the published pricing model starts at $10 per one million task runs, with the first 100,000 runs free.
Market
Hatchet competes in developer infrastructure for workflow orchestration, durable execution, distributed task queues, and AI-agent operations. Its comparison set includes Temporal and Inngest, as well as other durable-execution platforms, but Hatchet differentiates around open-source self-hosting, production-scale parallelism, fine-grained concurrency and fairness controls, and a unified experience for AI agents, background jobs, and mission-critical workflows.
The company is not merely pre-product: Hatchet was founded in 2023, joined Y Combinator’s Winter 2024 batch, and has a managed Cloud business alongside its open-source project. Its documentation reports billions of tasks processed per month, more than 10,000 open-source deployments per month, and hundreds of companies using Hatchet Cloud; its site also states that AI-first companies run more than 100 million tasks per day on the platform. These figures indicate meaningful adoption, although no revenue or valuation figure is provided in the available research.
Founders & Leadership
Funding History
Y Combinator
Recent News
Hatchet explains how idempotency keys let API handlers and downstream consumers deduplicate messages delivered more than once.
Hatchet announced new multi-team and enterprise-readiness capabilities for its orchestration platform, which supports AI agents, background tasks, and mission-critical workflows.
Hatchet published a practical guide to preventing Postgres reliability problems, focusing on query performance, indexes, tables, and primary keys.
This platform release added independent OLAP and core data-retention settings, tenant tagging and consolidated Hatchet Cloud settings, automatic Go SDK stream-listener reconnection, and RSS feeds for changelog and cookbook updates.
The release focused on stability for long-running deployments, including stricter duration validation and cleanup of expired or invalid user sessions to address unbounded session-table growth.
Hatchet Cloud introduced organization-level billing, giving customers one place to manage billing and resource limits across all tenants in an organization.
A Hacker News discussion covered Hatchet’s approach to building durable workflows on Postgres, with a Hatchet engineer participating in the discussion about the architecture.
Hatchet examined the operational risks and unexpected behavior involved in implementing database partitioning directly in Postgres.
Hatchet explained durable execution as a way to resume programs from their last checkpoint after failures, supporting more reliable long-running workflows.
Ubicloud published a customer story about Hatchet’s migration of core databases to Ubicloud. The story reports that Hatchet runs more than 100 million tasks per day, eliminated IOPS bottlenecks during 10x traffic spikes, and reduced annual database costs by more than $300,000, with nearly $500,000 projected after further migration.
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Get notified when they postBusiness Model
Hatchet monetizes its managed Hatchet Cloud service through usage-based task-run charges and paid monthly plans: Developer is free plus usage, Team is $500 per month plus usage, and Scale is $1,000 per month plus usage. Enterprise customers receive custom pricing and deployment, support, compliance, and service-level options, while the core platform is also open-source and self-hostable.