Parallel AI execution
Many minds,
one task.
Put a team of AI helpers to work in parallel.
Agent workflows takes a big job and splits it into independent parts, dispatches them to run simultaneously, and gathers the results into a structured report. Instead of one assistant grinding through a problem step by step, you get a coordinated team — each handling its own slice, all at once.
Agents at work
Each agent gets a scoped assignment. The pieces stay separate, run concurrently, and report back independently.
How it works
01
Parallel fan-out
One request becomes many. The work is broken into independent parts and dispatched to run simultaneously. No sequential bottleneck — all agents start at once.
02
Delegation
Each part is handed to its own helper with a clear, scoped assignment. The pieces stay separate so they don't step on each other's context or results.
03
Structured results
Findings come back in a consistent, machine-readable shape — ready to combine, review, or feed into downstream automation. Every result is independently verifiable.
The flow of a job
A large task enters the system. The coordinator splits it into parts that can stand on their own — each part self-contained enough that agents don't need to coordinate mid-flight. Every part is assigned to an agent and all run at once. Each agent returns a structured result; the coordinator gathers them into one report.