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Industries / Retail & E-commerce / Inventory-forecast agent

Retail AI agent · Inventory forecast

Inventory-Forecast AI Agent

Forecast demand from your own sales and supply history, publish a shippable quantity distinct from the forecast, and leave the committed plan and the purchase order to the people who sign them.

4–6 weeksTypical delivery
Your stackDeployment
Proposal-onlyDemand planner
Agent CareAfter launch

What this agent does

Forecasts the demand, not the commitment

In
01

Ingest sales history, on-hand positions, open purchase orders and supplier lead times from supported planning.

02

Normalise units, calendars and locations, and carry each figure forward with the system it came from.

Reason
03

Produce a demand forecast per item and location, with its error band and the horizon it holds for.

04

Apply the coverage, safety-stock and lead-time rules configured for that category and that supplier.

05

Derive a shippable quantity from stock the plan has actually secured, and keep it apart from the forecast.

Decide
06

Mark items whose ship-date promise rests on stock nobody has yet committed.

07

Route every reorder proposal to the demand planner and every commitment to the category buyer.

Out
08

Retain the inputs, the forecast version, the planner's overrides and the approval against the plan.

09

Execute write actions only inside the approval boundaries agreed during implementation.

Product statement

The agent proposes a plan; the demand planner approves it, the category buyer signs the purchase commitment, and the retailer answers for the promise.

Example workflow

One item-location, history to plan

AgentHuman
1Demand signal receivedSales history, on-hand position, open purchase orders or a supplier lead-time feed
2Inputs assembledCoverage rules, lead times, the promotion calendar and the stock already committed elsewhere
3Forecast producedDemand forecast, shippable quantity, error band and confidence
4Coverage checks runCoverage checks, allocation-rule checks, emergency-declaration checks and the confidence threshold
No human action required

Stages one to four run unaided, and nothing is bought at any of them — the agent is planning, and the planner's lane opens at the confidence gate.

5DecisionBranches on the coverage threshold
Inside tolerance

Goes to the demand planner to approve.

Outside tolerance

Adds a category-buyer read first.

Planner approval

The plan is held with its inputs, its shippable quantity and the confidence.

Approve · Adjust · Send to buyer review
Approved — released to commit
6Planning systems updatedOnly where write access and approval policy allow it
7Cycle evaluatedForecast error, override rate, coverage breaches and markdown taken after the fact
Overrides

Every planner override is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required8 items
Approving the committed demand plan.
Signing the purchase commitment.
Setting or changing price during a declared emergency.
Posting any inventory reserve or write-down.
Automation boundaryAgent acts unaided
Refresh statistical baselines and recompute forecast error by item.
Flag items breaching coverage or excess thresholds.
Draft reorder proposals into the planner's queue.
Reconcile the forecast against actual and log the variance drivers.
Any write happens inside the boundaries agreed at implementation, never ahead of the planner's approval.
Approving the scarcity allocation ruleset.
Onboarding any external market-data feed.
Publishing a customer-facing restock or ship date.
Overriding the compliance gate on a restricted item.

Example output

One item-location plan, annotated

Everything the agent proposes is attached to the record it was drawn from.

Forecast output · single item-locationIllustrative example
Item
Forecast line
Shippable now
Source of record
Confidence
Where it went
Seasonal apparel
Demand above the coverage band across the horizon, on a first-time long-lead supplier
1,240 units
Planning system and supplier feed
88%
Planner's queue
As receivedTaken from the planning system and the supplier's lead-time feed.
Evidence used Sales history Open purchase orders Supplier lead time
Why this quantityThe shippable figure counts only stock the plan has secured.
ActionApproveAdjustSend to buyer review
What the score decidesBelow the configured threshold the plan picks up a buyer read before it reaches the planner.

Value

Where AI adds value

The same four claims, placed at the point in the workflow where each one applies.

Where the value landsValue 01 – 04
Every item-locationFrom the planning system
03Forecasting

Plan from the record

Draw on sales history, open orders and supplier lead times, and on the coverage rules configured for that category.

01Approved path

Buy what will actually sell

Routine coverage checks and reorder proposals arrive already calculated.

02Human review

Send review to the exposed items

The Mail Order Rule wants a reasonable basis for a ship-date promise at the moment the order is solicited, so items resting on unsecured stock are marked and the planner reads those first.

04Build an evidence trail

Every plan keeps its inputs, its overrides and the planner who approved it.

Integrations

Typical integrations

Five system groups connect to the same agent. Which of them are in scope is decided in discovery.

Planning and forecastingBlue Yonder · o9 Solutions
Kinaxis · RELEX Solutions
ERP and inventorySAP IBP · Oracle NetSuite
Microsoft Dynamics · Infor
Commerce and ordersShopify · BigCommerce
Amazon Seller Central

Agent

Inventory forecasting and replenishment

Reads the history
Proposes the plan
Holds for approval

Supplier and purchasingCoupa · SAP Ariba
EDI purchase-order feeds
Observability & evaluationOpenTelemetry · Langfuse
Supported monitoring/evaluation sources

Integration availability depends on the client's existing systems and API access.

Agent controls

Six layers between the model and the buy

Controls nest inward. What a layer cannot see is named below.

L6 · Outermost — last line of defenceInward → L1 · closest to the model
L6Rollback / safe modeDrop to draft plans when evaluation or production signals degrade.Roll back
L5Version monitoringTrack model, prompt, coverage-rule and lead-time-configuration changes.Track
L4TraceabilityRecord the inputs, the forecast version, the overrides and the approval time.Record
L3Planner approvalHold plans for the named demand planner; it governs the commitment, not whether the forecast underneath it is right.Gate
L2Policy guardrailsTest plans against coverage rules, allocation rules and emergency-declaration state; a failure returns the plan.Restrict
L1Confidence thresholdsRoute low-confidence plans to a buyer read before the planner sees them.Require review
Model corePlan produced — demand forecast, shippable quantity, error band and confidence
L1 – L2Test whether a plan may stand
L3Puts the commitment in a planner's hands
L4 – L5Keep the version that fed the commitment
L6Drops to draft plans when signals degrade

How Nestack evaluates it

Evaluate the whole planning path — not only the forecast at the end of it.

Coverage runs the whole depth of the workflow, and every layer is cut by slice.

Surface — the plan the buyer commits to
Depth of coverage ▼
E1Final-output evaluationDid the forecast hold inside its stated error band over the horizon?
E2Step-level evaluationDid the agent use the right history, coverage rules and lead-time configuration?
E3Tool evaluationDid it read and write the correct item, the correct location and the correct plan?
E4Confidence calibrationDo low-confidence forecasts actually attract more planner overrides?
E5Slice evaluationHow does forecast error change across specific item classes?
E6Business outcomeHow many plans needed an override, and how many ended in markdown?
Floor — the stock position that results

Failure modes

Where each failure originates in the agent

Seven modes mapped to where the plan breaks.

Agent lifecycleDirection of processing →
01 · Retrieval1 mode
FO-01

Stale on-hand snapshot

The forecast runs against stock already allocated elsewhere.

Stage gathersSales history, on-hand, open orders
02 · Reasoning2 modes
FO-02

Promotional spike read as baseline

A promotion becomes the durable baseline and the buy runs into markdown.

FO-03

Protect-the-largest-banner heuristic

Scarce stock favours affiliated buyers with no cost justification recorded.

Stage proposesDemand forecast, shippable quantity and confidence
03 · Tool / write2 modes
FO-04

Order above delegated authority

A purchase order is written from a cached authority table.

FO-05

Reserve posted to the ledger

A reserve adjustment bypasses the controller's queue.

Stage writesOnly where write access and approval policy allow it
04 · Output1 mode
FO-06

Internal number published

A restock estimate reaches storefront availability as a promise.

Stage returnsThe plan the planner approves and the buyer
05 · Change / Version1 mode
FO-07

Lead-time distribution shifts

A retrain drops safety stock network-wide and the version behind the last reserve is gone.

Stage tracksModel, prompt and it is logged.
Sev-1 · a held act performed by the agent Sev-2 · a wrong quantity reaches the buy Sev-3 · input degrades, plan routes to review

Affected slices

One class of item carries the error

Forecast error here is the deviation from actual demand across the plan horizon Nestack reports it by slice rather than in aggregate The cohorts that carry it are named, not averaged away..

Slice performance — reported separately, not only in aggregateIllustrative example
SliceFailure rateLift Lift vs. thresholdStatus
New items, long-lead, promoted6.6%3.5× Review
Seasonal items, emergency declared4.9%2.6× Review
Long-tail intermittent demand3.4%1.8× Watch
High-velocity domestic staples1.7%0.9× Normal
Bar: forecast-error lift vs. the all-SKU baseline · scale 0–4.0× · tick marks the 2.0× review threshold 2 of 4 slices over threshold

Evidence-linked improvement

The planner decides when a cycle is closed

Closing means the failure is now a case the next release is measured against That suite is what the following detection is measured against..

Improvement cycle · five stagesSwitchback — the path turns at Improve and returns at Learn
01Detect

Forecast error rises in one item class.

02Diagnose

The planner reads the plans and the inputs behind them until one cause is left standing.

03Improve

A version stamp and the source data travel with the correction.

04Verify

Release is held until the affected cases clear.

05Learn

Both the suite and the planning assumptions carry it from then on.

Learn → DetectThe return edge. The next detection runs against a suite this cycle lengthened.

Typical build scope

Twelve workstreams across six weeks

The build scope read against the delivery timeline. Week structure follows the six-week plan — discovery, sources, forecasting workflow, evaluation, integration, then production validation and handover.

Workstream Week 1Week 2Week 3Week 4Week 5Week 6
01Planning workflow discovery and boundary definition.
02Planning and demand-signal assessment.
03Coverage, safety-stock and lead-time rule mapping.
04History ingestion and unit normalisation.
05Forecasting logic.
06Confidence scoring and proposal routing.
07Planner approval workflow.
08Planning-system and purchasing integration.
09Forecast regression cases.
10Guardrails and commitment controls.
11Version-trail instrumentation.
12Deployment, documentation and Agent Care handover.
12 workstreams · 6 weeks · bar shows the weeks a workstream is active — several run in parallel Final scope and sequence confirmed in discovery

Engagement tiers

What each tier includes

Rows are the capabilities named in each tier's scope. Higher tiers include everything below them.

Capability✓ in scope · — not at this tier PilotOne category, one region ProductionProduction planning systems AdvancedMultiple banners / regions
Introduced at Pilot
Forecasting to your history and rules
Planner approval
Forecast-error baseline
Introduced at Production
Reporting by SKU class
Approval workflow in your systems
Approved write-back
Planning-system integration
Introduced at Advanced
Multi-region planning rules
Multi-stage planning approvals
High item volume
Enterprise planning controls
Build price From $5,000 From $8,000 Custom quote
Final build priceConfirmed after discovery based on integrations, workflow complexity, transaction volume, approval controls and deployment requirements.
Separate from buildBuild pricing is separate from recurring Agent Care, which covers managed monitoring, evaluations, incidents and verified improvements after launch.

What we need from you

What you bring, and what we build with it

Each input maps to a piece of build scope and a week in the delivery timeline.

You bringWe build with it
01Your item master and location structure History ingestion and unit normalisationWeek 1
02Representative sales and supply history Forecasting baseline and shippable-quantity derivationWeek 2
03Your coverage rules and allocation policy Coverage, allocation and lead-time mapping, and automation-boundary definitionWeek 1
04Access to relevant APIs, feeds or exports Planning, ERP and supplier-feed assessment, then integration setupWeek 2
05Buys you would take back Forecast cases and failure-mode testingWeek 4
06The limits on any committed buy Coverage thresholds, commitment routing and controlsWeek 3
07A named planner to approve the plan Planner approval workflow, then pilot and production validationWeeks 5–6
Nothing else is required Deployment, documentation and Agent Care handover are ours.

Delivery timeline

Four phases across six weeks

Weeks here are occupied, not allocated, and the fifth carries two phases because the work overlaps.

Phase W1W2W3W4W5W6
Discovery W1
Build W2 – W3
Evaluate W4 – W5
Pilot & Launch W5 – W6
Week focus W1Planning workflow discovery, rule mapping and the automation boundary W2Demand history in place, then a baseline W3Forecasting workflow, confidence logic and approval controls W4Forecast cases and commitment guardrails W5Planning-system integration, pilot categories and targeted corrections W6One planning cycle approved by the planner, then handover
Reading the bandA bar covers the weeks its work is named in, and nothing else.
At the end of W6Sign-off on a real plan, then continuous monitoring under Agent Care.
DurationSix-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · Retail AI agent

Build a forecasting agent around the planner who approves the buy.

Show us your history, your coverage rules and who signs the buy. Separate the shippable quantity from the forecast before either one reaches a storefront — the Mail Order Rule wants a reasonable basis for the ship-date promise at the moment the order is solicited, and the FTC grounds that basis in anticipated demand, inventory sufficiency and fulfilment capacity, so a short buy sitting behind a live ship window is already a violation before a carton moves. We map the workflow, set the automation boundary, and name what stays with the planner, the buyer and the controller.

Nestack Agents · Inventory forecasting and replenishmentAGT-RT-05 · Agent Care available after launch