Nestack Agent Care

Retail AI agent · Dynamic pricing

Dynamic-Pricing & Markdown AI Agent

Propose markdowns from your own sales history and genuinely public data, freeze anything a live emergency declaration reaches, and hold every price for the pricing manager who releases it.

4–6 weeksTypical delivery
Your stackDeployment
Own data onlyPricing manager
Agent CareAfter launch

What this agent does

Proposes the price, never releases it

In
01

Ingest sales, cost, stock and calendar data from the retailer's own systems and genuinely public sources.

02

Normalise the fields, and carry every input forward with the feed it came from.

Reason
03

Estimate demand and propose a markdown or a price move inside the approved band.

04

Apply the pricing rules, bands and channel-parity requirements configured for the banner.

05

Check the provenance of each input, and reject anything a competitor could have supplied.

Decide
06

Freeze any SKU that a live emergency declaration reaches in a served geography.

07

Route every proposed price to the pricing manager who releases it.

Out
08

Retain the inputs, the rule, the proposal, the approver and the geographies published to.

09

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

Product statement

The agent proposes a price; the pricing manager releases it — and algorithmic pricing is now an antitrust question, not only a commercial one.

Example workflow

One price change, input to release

AgentHuman
1Price trigger receivedA markdown calendar, a stock position, a cost change or a rule review
2Inputs gatheredSales history, stock, cost, calendar and published list prices, each with its feed
3Price proposedOld price, new price, the rule that produced it, the channels and confidence
4Guardrails appliedProvenance checks, band checks, emergency-declaration checks, channel parity and confidence threshold
No human action required

Stages one to four run unaided and no price moves at any of them — the agent is proposing, and the pricing manager's lane opens at the confidence gate.

5DecisionBranches at the price guardrail
Inside the guardrail

Goes to the pricing manager to release.

Outside the guardrail

Adds a legal read first.

Pricing-manager approval

The change is held with its inputs, their provenance and the confidence.

Approve · Adjust · Send to legal review
Approved — released to publish
6Price systems updatedOnly where write access and approval policy allow it
7Change evaluatedMargin and sell-through, gate failures, channel divergence and post-release corrections
Rollbacks

Every pricing-manager adjustment is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required8 items
Releasing any price to a live channel.
Approving a move outside the agreed band.
Onboarding a new price feed or data source.
Pricing on any input drawn from an identifiable shopper.
Automation boundaryAgent acts unaided
Estimate demand from the retailer's own sales history for the named owner.
Propose markdowns inside the approved band and queue.
Reconcile shelf, till.
Freeze a SKU when a legal gate fails, and hold it for approval.
Any write happens inside the boundaries agreed at implementation, never ahead of approval.
Wording and placement of an algorithmic-pricing disclosure.
Certifying a former price before a strike-through runs.
Accepting a vendor model or rule-set upgrade.
Remediation after a wrong price has been charged.

Example output

One price change, annotated

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

Pricing output · single SKUIllustrative example
SKU
Proposed change
New price
Input provenance
Confidence
Personal data
Seasonal apparel line
Markdown inside the approved band for the clearance window
$34.00
Own sales history
93%
None used
As receivedTaken from the retailer's own systems and published list prices.
Inputs used Own sales history Stock and cost position Published list price
Why this priceIt sits inside the band the pricing manager approved — the move they weigh.
ActionApproveAdjustSend to legal review
What the score decidesBelow the configured threshold the change picks up a legal read before it reaches the pricing.

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 price changeFrom the retailer's own systems
03Proposal

Price from your own data

Draw on first-party sales, cost and stock, and the bands the pricing manager approved.

01Approved path

Move the price, keep the record

Routine markdowns inside the band arrive already worked out.

02Human review

Send review to the risky moves

Gate failures and low-confidence proposals are marked, so the pricing manager's read starts where exposure concentrates.

04Build an evidence trail

Each price keeps its rule, its inputs and the approver who released it.

Integrations

Typical integrations

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

Price and markdown optimisationRevionics · Blue Yonder Pricing
Pricefx · PROS
Price science and lifecycleDemandTec / Acoustic · Zilliant
Eversight · Bloomreach
Published-price monitoringCompetera · DataWeave
Public list and ad feeds

Agent

Dynamic pricing & markdown

Reads your own data
Proposes the price
Holds for approval

Channels and workflowPrice book · POS · ESL feed
Web PDP · marketplace · ad 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 shelf

Each control contains the next; the map below names the gaps.

L6 · Outermost — last line of defenceInward → L1 · closest to the model
L6Rollback / safe modePull pricing back to proposal-only when evaluation or production signals degrade.Roll back
L5Version monitoringTrack model, prompt, rule-band and jurisdiction-configuration changes.Track
L4TraceabilityRecord the inputs, their provenance, the rule, the approver and the release time.Record
L3Pricing approvalHold changes for the named pricing manager; it governs release, not whether an approved price is right.Gate
L2Policy guardrailsTest proposals against feed provenance, band, emergency and parity rules; a failure freezes the SKU.Restrict
L1Confidence thresholdsRoute low-confidence proposals to a legal read before the pricing manager sees them.Require review
Model corePrice proposed — old price, new price, the rule, the channels and confidence
L1 – L2Test whether a price may stand
L3Puts the release in a pricing manager's hands
L4 – L5Hold the price history and the rule behind it
L6Freezes prices at the last approved set

How Nestack evaluates it

Evaluate the pricing workflow — not only the final number.

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

Surface — the price the shopper pays
Depth of coverage ▼
E1Final-output evaluationDid the published price clear every gate it had to clear?
E2Step-level evaluationDid the agent use the right inputs, bands and jurisdiction configuration?
E3Tool evaluationDid it write the correct SKU and the correct channel?
E4Confidence calibrationDo low-confidence proposals actually attract more adjustments?
E5Slice evaluationHow does performance change across specific price cohorts?
E6Business outcomeHow many changes needed an adjustment or a correction after release?
Floor — the price that is charged

Failure modes

Where each failure originates in the agent

Seven modes plotted against the pricing lifecycle.

Agent lifecycleDirection of processing →
01 · Retrieval1 mode
DP-03

Competitor feed ingested

A co-listed seller's promotional calendar is read as market data.

Stage gathersSales history, stock, cost, with the source each came from
02 · Reasoning2 modes
DP-04

Emergency read as seasonality

Demand under a declared emergency is priced as an ordinary spike.

DP-06

Former price reconstructed

A one-day reversal is taken as the price regularly offered.

Stage proposesOld price, new price, the rule and confidence
03 · Tool / write2 modes
DP-02

Disclosure not emitted

A personalised markdown publishes without the required label.

DP-05

Channels left divergent

Shelf and web take the new price while the price book times out.

Stage writesOnly where write access and approval policy allow it
04 · Output1 mode
DP-01

Former price unsupported

A strike-through renders against a price too old to support it.

Stage returnsThe price the shopper is charged
05 · Change / Version1 mode
DP-07

Silent targeting regression

A vendor update re-enables geography below the level configured.

Stage tracksModel, prompt, rule bands and jurisdiction config
Sev-1 · a price released outside the boundary Sev-2 · a non-compliant price reaches a channel Sev-3 · a feed degrades, the SKU freezes

Affected slices

Overall compliance can hide one cohort

An aggregate gate-failure rate can look settled while one cohort of price changes carries almost all of it. Nestack reports that rate by slice as a lift on the all-price-change.

Slice performance — reported separately, not only in aggregateIllustrative example
SliceFailure rateLift Lift vs. thresholdStatus
Emergency geographies, personalised5.4%2.7× Review
Strike-through in strict states4.2%2.1× Review
Shared-engine concentrated categories2.4%1.2× Watch
Single-channel, non-personalised1.2%0.6× Normal
Bar: gate-failure lift vs. the all-price-change baseline · scale 0–4.0× · tick marks the 2.0× review threshold 2 of 4 slices over threshold

Evidence-linked improvement

A cycle is not closed by a fix

What closes a cycle is a case in the suite, not agreement about what went wrong That suite is what the following detection is measured against..

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

Gate failures rise in one price cohort.

02Diagnose

Until the cause narrows to a single feed, rule or prompt, the pricing manager keeps reading the runs behind the failures.

03Improve

Each change is version-stamped and linked to the run that surfaced it.

04Verify

The release waits on the affected cases passing again.

05Learn

It becomes a permanent case and a change to the pricing guardrails.

Learn → DetectThe return edge. Detection next time runs against a longer suite than this one.

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, pricing workflow, evaluation, integration, then production validation and handover.

Workstream Week 1Week 2Week 3Week 4Week 5Week 6
01Pricing workflow discovery and boundary definition.
02Price-engine and margin-source assessment.
03Rule, band and jurisdiction mapping and rule mapping.
04First-party sales, stock and cost ingestion.
05Proposal logic and input-provenance.
06Confidence scoring and gate-failure routing.
07Pricing-manager approval.
08Price-book, shelf and channel integration.
09Pricing regression cases.
10Guardrails and release controls.
11Price-history 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 banner, one channel ProductionProduction price systems AdvancedMultiple banners / markets
Introduced at Pilot
Proposals to your rules and bands
Pricing-manager approval
Price-integrity baseline
Introduced at Production
Reporting by category
Approval workflow in your systems
Approved write-back to price systems
Price-engine integration
Introduced at Advanced
Multi-banner rule sets
Multi-stage pricing approvals
High SKU and channel volume
Enterprise pricing 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 price rules, bands and markdown calendar Rule, band and jurisdiction mappingWeek 1
02Representative past price changes Proposal baseline, elasticity and provenance bindingWeek 2
03The feeds you price from, and where each one comes from Rule and band mapping, and the automation boundaryWeek 1
04Access to relevant APIs, feeds or exports Price-engine, POS and channel assessment, then integration setupWeek 2
05Prices that should not have gone live Pricing cases and failure-mode testingWeek 4
06Which prices may never move unattended Guardrail bands, release routing and controlsWeek 3
07A named pricing manager to release prices Pricing-manager 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

Phases occupy real weeks, and evaluation overlaps launch in the fifth rather than being stretched.

Phase W1W2W3W4W5W6
Discovery W1
Build W2 – W3
Evaluate W4 – W5
Pilot & Launch W5 – W6
Week focus W1Pricing workflow discovery, rule mapping and the automation boundary W2Cost and competitor-public feeds in place W3Proposal workflow, confidence logic and release controls W4Pricing cases and release guardrails W5Channel integration, pilot price changes and targeted corrections W6A live pricing cycle released by the pricing manager, then handover
Reading the bandEach bar spans only its named weeks; the overlap in week 5 is real work.
At the end of W6A verified cycle in production, then monitoring sits with Agent Care.
DurationSix-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · Retail AI agent

Build a pricing agent that can show where every input came from.

Show us the feeds you price from, the bands you work inside and who releases a change. A price that has already been charged cannot be unwound by a refund alone, so we set the provenance, emergency and disclosure gates before anything moves.

Nestack Agents · Dynamic pricing and markdownAGT-RT-08 · Agent Care available after launch