// the problem

Supply chains run on dozens of disconnected decisions a day

Demand shifts, a shipment slips, a supplier misses a confirmation. Each event needs a decision, and those decisions live in inboxes, spreadsheets, and the head of whoever is on shift. There is no shared picture of what is happening, who decided what, or why.

Bolting a single AI agent onto one task does not fix this. The hard part is coordination: many agents, watching many signals, making decisions that have to be governed, auditable, and consistent with each other.

// how it solves it

The nerve center for a fleet of agents

The Orchestrator gives a fleet of AI agents a shared model of the supply chain - the nodes, lanes, flows and business objects they all act on - and a single place to run. Agents wake on a heartbeat, watch for signals, propose decisions, and act within the limits you set.

Every decision passes a policy check before it executes and is written to an immutable trace, so you can follow any outcome back through its trigger, analysis, approval and result. Nothing happens off the books.

// architecture overview

Sense, decide, govern, trace

01
SenseAgents wake on a heartbeat and read one shared supply-chain model; signals flow through an event bus
→
02
DecideEach agent analyses its signals and proposes a decision within its stage: anticipate, acquire, transform, fulfill, recover
→
03
GovernA policy layer checks every decision: auto-approve, route to a human, or block
→
04
Act & traceApproved decisions execute and are recorded as immutable traces, with full provenance across agents and stages

A maturity model controls autonomy per agent: from "every decision needs approval" up to "fully autonomous, with audit".

// what makes it different

Coordination and governance, not a single bot

shared model
One shared world model

Every agent reads and writes the same supply-chain model - nodes, lanes, flows and business objects - so decisions stay consistent instead of siloed per tool.

governed
Governed by default

A policy layer sits in front of every action. You decide what auto-approves, what needs a human, and what is blocked - per agent, stage or node.

traceable
Fully traceable

Every decision is an immutable trace from trigger to outcome. You can prove what happened, who decided, and why, across the whole fleet.

maturity
Maturity, not all-or-nothing

Agents earn autonomy level by level. Start with everything gated and move to hands-off only where the track record supports it.

// features & updates pipeline

Where The Orchestrator is heading

in progressControl room

A live control room for the fleet: agent status board, decision queue, event timeline and an impact dashboard, so an operator can see and steer everything from one screen.

plannedFleet scaling

Grow from a handful of reference agents to a managed fleet across every stage of the chain, deployed and budgeted as a unit.

plannedOpen agent connection

Connect any compliant agent over standard protocols (MCP and agent-to-agent), with no custom adapters to maintain.