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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.

Typical delivery
4–6 weeks
Deployment
Your stack
Demand planner
Proposal-only
After launch
Agent Care

What this agent does

Forecasts the demand, not the commitment

In

  1. 01

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

  2. 02

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

Reason

  1. 03

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

  2. 04

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

  3. 05

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

Decide

  1. 06

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

  2. 07

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

Out

  1. 08

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

  2. 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

  1. 1Demand signal receivedSales history, on-hand position, open purchase orders or a supplier lead-time feed
  2. 2Inputs assembledCoverage rules, lead times, the promotion calendar and the stock already committed elsewhere
  3. 3Forecast producedDemand forecast, shippable quantity, error band and confidence
  4. 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

  1. 6Planning systems updatedOnly where write access and approval policy allow it
  2. 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 required

8 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 boundary

    Agent 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-location

Illustrative example
Item
Seasonal apparel
Forecast line
Demand above the coverage band across the horizon, on a first-time long-lead supplier
Shippable now
1,240 units
Source of record
Planning system and supplier feed
Confidence
88%
Where it went
Planner's queue

As received

Taken from the planning system and the supplier's lead-time feed.

Evidence used

  • Sales history
  • Open purchase orders
  • Supplier lead time

Why this quantity

The shippable figure counts only stock the plan has secured.

What the score decides

Below the configured threshold the plan picks up a buyer read before it reaches the planner.

Action

ApproveAdjustSend to buyer review

Value

Where AI adds value

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

Where the value lands

Value 01 – 04

Every item-location

From 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.

04

Build 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 forecasting

    • Blue Yonder
    • o9 Solutions
    • Kinaxis
    • RELEX Solutions

  • ERP and inventory

    • SAP IBP
    • Oracle NetSuite
    • Microsoft Dynamics
    • Infor

  • Commerce and orders

    • Shopify
    • BigCommerce
    • Amazon Seller Central

Agent

Inventory forecasting and replenishment

  • Reads the history
  • Proposes the plan
  • Holds for approval

  • Supplier and purchasing

    • Coupa
    • SAP Ariba
    • EDI purchase-order feeds

  • Observability & evaluation

    • OpenTelemetry
    • 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 defence

Inward → 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 – L2
Test whether a plan may stand
L3
Puts the commitment in a planner's hands
L4 – L5
Keep the version that fed the commitment
L6
Drops 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

  1. E1Final-output evaluationDid the forecast hold inside its stated error band over the horizon?
  2. E2Step-level evaluationDid the agent use the right history, coverage rules and lead-time configuration?
  3. E3Tool evaluationDid it read and write the correct item, the correct location and the correct plan?
  4. E4Confidence calibrationDo low-confidence forecasts actually attract more planner overrides?
  5. E5Slice evaluationHow does forecast error change across specific item classes?
  6. 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 lifecycle

Direction of processing →

  1. 01 · Retrieval

    1 mode

    • FO-01

      Stale on-hand snapshot

      The forecast runs against stock already allocated elsewhere.

    Stage gathers

    Sales history, on-hand, open orders

  2. 02 · Reasoning

    2 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 proposes

    Demand forecast, shippable quantity and confidence

  3. 03 · Tool / write

    2 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 writes

    Only where write access and approval policy allow it

  4. 04 · Output

    1 mode

    • FO-06

      Internal number published

      A restock estimate reaches storefront availability as a promise.

    Stage returns

    The plan the planner approves and the buyer

  5. 05 · Change / Version

    1 mode

    • FO-07

      Lead-time distribution shifts

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

    Stage tracks

    Model, 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
See the complete Retail failure-mode catalogue

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 aggregate

Illustrative example
SliceFailure rateLiftLift 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 stages

Switchback — the path turns at Improve and returns at Learn

  1. 01

    Detect

    Forecast error rises in one item class.

  2. 02

    Diagnose

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

  3. 03

    Improve

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

  4. 04

    Verify

    Release is held until the affected cases clear.

  5. 05

    Learn

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

  6. Learn → Detect

    The 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

  1. 01Planning workflow discovery and boundary definition.Week 1
  2. 02Planning and demand-signal assessment.Week 1, Week 2
  3. 03Coverage, safety-stock and lead-time rule mapping.Week 1, Week 2
  4. 04History ingestion and unit normalisation.Week 2
  5. 05Forecasting logic.Week 2, Week 3
  6. 06Confidence scoring and proposal routing.Week 3
  7. 07Planner approval workflow.Week 3, Week 4
  8. 08Planning-system and purchasing integration.Week 5
  9. 09Forecast regression cases.Week 4, Week 5
  10. 10Guardrails and commitment controls.Week 4
  11. 11Version-trail instrumentation.Week 5, Week 6
  12. 12Deployment, documentation and Agent Care handover.Week 6

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 tierPilotOne category, one regionProductionProduction planning systemsAdvancedMultiple 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 priceFrom $5,000From $8,000Custom quote
Final build price
Confirmed after discovery based on integrations, workflow complexity, transaction volume, approval controls and deployment requirements.
Separate from build
Build 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.

  1. 01Your item master and location structure

    History ingestion and unit normalisation

    Week 1

  2. 02Representative sales and supply history

    Forecasting baseline and shippable-quantity derivation

    Week 2

  3. 03Your coverage rules and allocation policy

    Coverage, allocation and lead-time mapping, and automation-boundary definition

    Week 1

  4. 04Access to relevant APIs, feeds or exports

    Planning, ERP and supplier-feed assessment, then integration setup

    Week 2

  5. 05Buys you would take back

    Forecast cases and failure-mode testing

    Week 4

  6. 06The limits on any committed buy

    Coverage thresholds, commitment routing and controls

    Week 3

  7. 07A named planner to approve the plan

    Planner approval workflow, then pilot and production validation

    Weeks 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

W1

W2

W3

W4

W5

W6

  1. DiscoveryW1
  2. BuildW2 – W3
  3. EvaluateW4 – W5
  4. Pilot & LaunchW5 – 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 band
A bar covers the weeks its work is named in, and nothing else.
At the end of W6
Sign-off on a real plan, then continuous monitoring under Agent Care.
Duration
Six-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.

Typical delivery
4–6 weeks
Deployment
Your planning stack
Demand planner
Proposal-only
After launch
Agent Care available

Nestack Agents · Inventory forecasting and replenishment

AGT-RT-05 · Agent Care available after launch

Build a forecasting agent

Four questions so the call starts from your actual setup — then pick a time that suits you.

About you
Your inventory

No obligation. We’ll map the workflow, name the automation boundary and tell you if an agent is the wrong answer.