Parallel Workloads
Process thousands of documents, enrich large datasets, and run agent swarms without the operational complexity.
Our AI agents process hundreds of thousands of documents for our customers, including leading financial institutions and corporations. Hatchet's parallelization feature allows us to ingest massive amounts of data from these documents and simultaneously execute next steps, quickly and reliably at scale.
Athos CoutoEnterWith Hatchet, we’ve scaled our indexing workflows effortlessly, reducing failed runs by 50% and doubling our user base in just two weeks!
Soohoon ChoiGreptileHatchet enables Aevy to process up to 50,000 documents in under an hour through optimized parallel execution, compared to nearly a week with our previous setup.
Ymir EgilsonAevyFan out to thousands of workers
Fan out to thousands of workers with a single function call. Built-in fairness algorithms and resource management ensure efficient utilization without manual intervention.
Process entire document repositories in parallel
Enrich millions of leads without rate limit headaches
Scrape data with automatic retry and deduplication
Full visibility into every run
See every worker, task, and failure in the Hatchet dashboard. Get alerts when jobs stall, replay failed batches with a single click, and export metrics to your existing monitoring stack.
Real-time visibility into every task and worker execution
Replay any failed batch directly from the UI
Export metrics to Datadog, Grafana, or any OTEL collector
Works with your stack and infrastructure
Hatchet SDKs are language-native — no DSLs, no YAML, no new paradigms to learn. Workers run as standard long-lived processes and deploy on the container platform you already use.
Languages
Infrastructure
Scale without limits. Stop managing orchestration infrastructure and start shipping faster.
Start for free — no credit card required
Processing over 100 million tasks/day for AI-first companies
Enterprise-grade security, compliance, and SSO