An AI-native planning engine that answers the three questions every manufacturer asks: which orders ship on time, what material is short and why, and what to buy and when — with full traceability to prove it. Currently in development — here's a first look at what's coming.
AIVA APS takes your factory's real snapshot — demand, inventory, purchase orders, WIP, BOM, lead times, calendars — and runs a complete material requirements planning engine. No spreadsheets. No guesswork.
Normalizes and prioritizes every demand source — MPS master schedules, sales orders, and forecasts — into a single ranked queue with configurable priority rules.
Pools on-hand inventory, in-transit shipments, open POs, and existing manufacturing orders — then allocates to demand by priority, availability date, and material attributes.
Processes multi-level bills of material top to bottom — handling phantom items, engineering changes, alternative materials, and intermediate inventory offsets at every level.
Schedules backward from due dates and forward from real material availability — then picks the honest planned start based on what's actually possible, not what you wish were true.
Identifies exactly which materials are short, how much is missing, which orders are impacted, and whether the shortage is structural (lead time exceeds the window) or solvable.
Generates actionable purchase suggestions — which item, from which supplier, when to release, when it arrives — respecting MOQ, lot sizes, lead times, and receiving dock calendars.
AIVA APS runs a complete planning engine against your factory snapshot. Each stage feeds the next — no manual handoffs, no intermediate exports.
Freeze demand, supply, BOM, routings, calendars & parameters into a reproducible planning run.
Prioritize demand, match planning attributes, search primary & alternative supply by time bucket.
Explode multi-level BOMs, schedule backward from due dates and forward from real material availability to find honest planned dates.
Create planned production & procurement orders. Build full demand-to-supply traceability across all BOM levels.
Automated validation — demand coverage, quantity checks, supply realism, delivery performance — then publish results.
Physically honest. AIVA APS never hides lateness. If supply can't arrive before the due date, the plan says so — giving you time to act instead of a false sense of security. Every timing calculation respects factory calendars, receiving dock days, and supplier lead times from your master data.
Traceability is a first-class output, not an afterthought. AIVA APS records the complete supply-demand relationship across every BOM level — so you can trace any shortage back to its root cause and any procurement recommendation back to the demand that triggered it.
Start from any sales order and trace down: which production orders serve it, what components they need, where each material comes from — inventory, PO, planned procurement, or shortage.
Start from any supply — a delayed PO, a depleted stock lot — and trace up to every demand it impacts. Know immediately which customers feel it.
Every allocation link records the type, quantity, timing, rule applied, priority rank, and reason. Quantities are validated automatically: nothing gets lost or double-counted.
Why pegging matters: When a supplier says "your PO is delayed 5 days," pegging tells you in seconds which sales orders are impacted, which production orders are waiting, and whether the delay cascades into customer-facing lateness — or is absorbed by buffer time. No manual tracing. No guesswork.
AIVA APS produces structured decision-support outputs — each one answering a specific question your planning team asks every day.
| Output | Answers |
|---|---|
| Master Schedule | Every demand's completion date vs. due date — on time or late, and by how much. |
| Short Orders | Which materials are short, how much is missing, and which demand caused the shortage. |
| Procurement Plan | What to buy, from which supplier, when to release the PO, and when material arrives — with late-arrival alerts when arrival exceeds need date. |
| Production Timing | Planned start vs. latest start for every manufacturing order — highlighting orders that can't start on time due to material constraints. |
| Traceability Map | The full demand-to-supply causation tree — multi-level, multi-source, with ECN substitution paths and quantity validation at every link. |
| Delivery Performance | On-time delivery rates by scope (SO, forecast, all), week-rolling trend, with V4 physical-honesty scoring. |
AIVA APS includes an AI planning agent that answers questions grounded in your actual plan data and traceability — not generic model knowledge. And a what-if workbench that lets planners test scenarios before committing.
The agent traces the supply chain, identifies the constraining material, shows the supplier lead time vs. the available window, and explains whether the delay is structural or solvable.
Positive actions (expedite, air-ship, substitute material) run in seconds. Disruptive changes (rush orders, supply reallocation) trigger a full re-plan with before/after comparison.
Every planning run is snapshotted and versioned. Compare two versions side-by-side — which orders improved, which degraded, what supply changed — with full evidence for each delta.
Questions the agent answers: Why is this sales order late? Which supply fulfills this demand? Which PO delay impacts which orders? What planned procurement was created and why? What changed between two plan versions? — Every answer cites specific data from your plan, not general knowledge.
AIVA APS implements a comprehensive set of business rules refined against real factory data — covering edge cases that spreadsheet-based planning and generic MRP systems miss.
MPS master schedules, sales orders, and forecasts each follow distinct due-date conventions. AIVA APS normalizes them into one ranked priority queue while preserving source traceability.
Engineering change notices with effectivity dates, alternative material rules, and old/new part convergence — so shortage detection doesn't create false positives from part-number transitions.
Supply is pooled and allocated by priority — not locked to individual orders. MTO surplus flows back to the shared pool after bound demand is satisfied, maximizing material utilization.
Factory calendars, shift patterns, receiving dock working days, and supplier lead times are all read from master data — never hardcoded. Reruns are reproducible against the same snapshot.
No POs in the past. Same-week same-item consolidation. MOQ and lot-size rules. Release-date clamping. Arrival-vs-need late alerts. Supplier-specific lead times from vendor master.
Every demand accounted for. Quantities balanced across the plan. Real vs. planned supply clearly separated. Delivery performance tracked weekly. No unchecked gaps.
The material planning core is under active development. The engine is designed in layers — each one building on the last toward a full enterprise APS solution.
Demand planning, supply allocation, multi-level BOM processing, full traceability, intelligent scheduling, planned production & procurement, shortage detection.
Feasible time windows for production operations. Forward and backward propagation across operation precedence to eliminate impossible schedules before optimization.
Work center load profiles, overload detection, bottleneck identification, resource-constrained scheduling, and Gantt-ready operation timelines.
AIVA APS is available for early-access manufacturers. Talk to us about running it against your factory data.