Autonomous workflows
Compose reliable machines from models, APIs, people, and data. Every step is durable, resumable, and observable.
Transform fragmented tools, models, and teams into governed systems that sense, decide, and act—without losing human control.
control-plane target
policy evaluation
autonomous runtime
traceable actions
01 / The platform
Automation Machines gives operating teams the primitives to build autonomy into real systems—with the reliability, visibility, and governance production demands.
Compose reliable machines from models, APIs, people, and data. Every step is durable, resumable, and observable.
Place approvals, limits, and escalation paths exactly where risk enters the system.
Follow every decision from signal to outcome with live traces, costs, and system health.
Connect the stack you already run. Automation Machines stays model-agnostic, API-native, and infrastructure-flexible.
02 / Guided process
Start with the systems you have. Add intelligence deliberately. Move from assisted work to autonomy at the pace your operation can trust.
Step 01
Connect APIs, event streams, databases, and human inputs through one typed operational graph.
48.2k events/min
Live runtime measurement
03 / Applied autonomy
Move beyond demos. Build machines around the bottlenecks, exceptions, and high-frequency decisions that shape real operating performance.
Industrial operations
01operator time recovered / week
Illustrative deployment
Financial operations
02faster close triage
Illustrative deployment
Digital operations
03more volume per team
Illustrative deployment
04 / Control by design
Every machine ships with identity, permissions, audit trails, and intervention controls built into the runtime—not bolted on after deployment.
Every machine and operator acts through explicit, scoped identity.
Rules and thresholds are checked before consequential action.
Inputs, decisions, costs, and outcomes remain inspectable.
Pause, approve, redirect, or roll back from one control surface.
Initialize / AM-01