How agents take action.

The loop, end to end

ADIP agents work a three-beat loop. Sense: read live operational data — orders, inventory positions, supplier confirmations, capacity signals — from the systems you already run. Decide: weigh the options against your constraints, policies, and the judgment your planners have encoded, and price the alternatives. Act: write the chosen change back where it belongs — the purchase order re-dated in the ERP, the allocation adjusted in order management, the wave re-sequenced in the WMS — so the decision exists where work actually happens, not in a slide.

What write-back means, precisely

A write-back is a specific, bounded change to a system of record, proposed with its reasoning attached. Every write-back in ADIP has four properties:

• Proposed, not smuggled. The agent states the change, the alternatives it priced, and why this one. You can read the recommendation the way you'd read a colleague's.
• Approved at the level you choose. Routine, low-stakes changes can run within pre-agreed bounds; anything outside them waits for a human. Autonomy is a dial you set per decision type, not a switch someone else flipped.
• Logged with its rationale. Every change lands in an audit trail with the signal that triggered it, the options considered, and who (or what policy) approved it — so "why did this happen?" always has an answer.
• Reversible by design. A write-back targets fields and documents your team already governs; undoing one is an ordinary transaction, not an archaeology project.

The systems agents read and write

ADIP layers over your existing stack — it doesn't replace it. Agents connect to the categories of systems where supply chain decisions live:

• ERP — purchase orders, production orders, materials, pricing, master data.
• Order management — promise dates, allocations, holds and releases.
• WMS — inventory positions, waves, pick priorities.
• TMS — shipments, carrier selection, routing changes.
• Planning & MES — forecasts, schedules, production sequencing.

Integration is read-first: an agent earns write access one decision type at a time, after its recommendations have been watched and trusted in read-only mode. That's the same path a new planner walks — see the decision, explain the decision, then own the decision.

Bounded autonomy, governed by design

Action without governance is how AI projects get cancelled. ADIP treats governance as part of the write-back itself: which decision types an agent may touch, the bounds it may act within, what evidence it must attach, and when a human must intervene are explicit, reviewable policy — not tribal convention. The audit trail is the receipt.