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Electronics AI agent · Commerce

Commerce & Shopping AI Agent

Recommend from the attributes in your catalogue, hold to the review and disclosure rules you configured, and put a purchase to the shopper as its own authorisation the merchant can produce later.

Typical delivery
4–6 weeks
Deployment
Your stack
Shopper consent
Per-purchase
After launch
Agent Care

What this agent does

Ranks inside your catalogue; the shopper buys

In

  1. 01

    Catalogue records, price cards, stock and configured review rules, ingested from supported commerce or PIM sources.

  2. 02

    Attribute names and units normalised, with each value carried forward from the record it came from.

Reason

  1. 03

    A shortlist drawn from the catalogue, ranked on the attributes the shopper asked about.

  2. 04

    Brand, market and category rules applied as the merchant configured them.

  3. 05

    Comparisons built from attributes on the product card, with what the card leaves out marked as missing.

Decide

  1. 06

    Review content surfaced under the merchant's configured handling rules.

  2. 07

    An AI-system disclosure and any material connection shown in the session.

Out

  1. 08

    The recommendation, the attributes behind it and the shopper's authorisation retained together.

  2. 09

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

Product statement

The agent recommends and assembles; the shopper authorises the purchase, and the merchant of record still carries fraud and chargebacks.

Example workflow

One session, request to purchase

  1. 1Shopper request receivedStorefront chat, search, app session or a connected agent surface
  2. 2Catalogue readAttributes, price card, stock, configured review rules and the disclosure set
  3. 3Shortlist builtCandidates, attributes compared and confidence
  4. 4Controls appliedCatalogue-source checks, review-handling rules, disclosure checks and the confidence threshold

No human action required

Stages 1 to 4 run unaided and nothing is bought at any of them — the agent is recommending, and the shopper's lane opens at the confidence gate.

5DecisionSplits at the confidence threshold
High confidence

Goes to the shopper to authorise.

Low confidence

Adds a commerce-team check first.

Shopper authorisation

The basket is held with the attributes behind it, the total and the confidence.

Authorise · Amend · Hand to a person

Authorised — order placed

  1. 6Commerce systems updatedOnly where write access and merchant policy allow it
  2. 7Outcome evaluatedDisowned orders, returns, cancellations and corrections made after the order shipped

Amends

Each shopper amendment is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required

8 items

  • Completing a purchase or authorising a payment.
    • Enrolling a subscription, trial or auto-renewal.
    • Generating review content outside the configured rules.
    • Quoting a price that is not on the published card.

  • Automation boundary

    Agent acts unaided

    • ✓Search the configured catalogue and rank what matches the request.
    • ✓Compare candidates on attributes held in the catalogue.
    • ✓Assemble a basket and leave it with the shopper.
    • ✓Hold the order and put an itemised authorisation to the shopper.

    Any write happens inside the boundaries agreed at implementation, never ahead of authorisation.

    • Accepting merchant terms for the shopper.
    • Applying an eco, efficiency or certification label.
    • Trading where the platform's terms bar agents.
  • Changes to disclosure or recommendation rules.

Example output

One authorisation, annotated

What the agent ranked, and what the shopper authorised, stay attached to the session.

Recommendation output · single session

Illustrative example
Product
Mid-range laptop
Ranked line
Ranked first on the ports and weight the shopper asked about
Card price
$1,299.00
Attribute source
Published price card
Confidence
91%
Disclosure
AI system disclosed in session

As received

Read from the published product card and the stock feed — nothing on this side is written by the agent.

Attributes used

  • Card specification
  • Stock position
  • Return terms

Why this ranking

Ranked on the attributes the shopper named — fit stays their call.

What the score decides

Below the configured threshold the basket gets a commerce-team check first.

Action

AuthoriseAmendHand to a person

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 session

From the storefront

03Ranking

Rank inside the card

Draw on the attributes published on the card and the merchant's configured rules.

01Approved path

Recommend inside the catalogue

Routine product questions are answered from the catalogue itself.

02Human review

Push the risky calls to a person

Purchases and subscriptions are held for the shopper, because whether a wrong one is unauthorised is unsettled.

04

Build an evidence trail

The recommendation, the attributes it rested on and the authorisation for any purchase stay on the session.

Integrations

Typical integrations

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

  • Commerce platforms

    • Shopify
    • commercetools
    • Salesforce Commerce Cloud

  • Search and discovery

    • Algolia
    • Bloomreach
    • Constructor
    • Dynamic Yield

  • Product data

    • Akeneo
    • Salsify
    • PIM feeds
    • stock

Agent

Commerce and shopping

  • Reads the catalogue
  • Ranks candidates
  • Holds for authorisation

  • Reviews and payments

    • Bazaarvoice
    • Yotpo
    • Stripe
    • Adyen

  • 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 checkout

The controls are nested. What survives all of them appears in the map underneath.

L6 · Outermost — last line of defence

Inward → L1 · closest to the model

L6Rollback / safe modeDrop the agent to recommendation-only when evaluation or production signals degrade.Roll back
L5Version monitoringTrack model, prompt, disclosure-template and catalogue-rule changes.Track
L4TraceabilityRecord the attributes read, the ranking, the disclosure state and the consent.Record
L3Shopper consentHold the purchase for the shopper; it governs the order being placed, not whether the pick fits.Gate
L2Policy guardrailsTest output against the configured review, disclosure and price rules; a failure returns the basket.Restrict
L1Confidence thresholdsRoute low-confidence baskets to a commerce-team check before they are shown.Require review
Model coreBasket assembled — ranked candidates, the attributes compared and confidence
L1 – L2
Test whether a basket may stand
L3
Puts the purchase in the shopper's hands
L4 – L5
Show what the recommendation was built from
L6
Holds purchases for the shopper when signals degrade

How Nestack evaluates it

Evaluate the whole session — not only the product that came top.

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

Surface — what the shopper is shown

  1. E1Final-output evaluationDid each attribute the agent stated match the card?
  2. E2Step-level evaluationDid the agent use the right catalogue, review rules and disclosure set?
  3. E3Tool evaluationDid it read the right product and write to the right basket?
  4. E4Confidence calibrationDo low-confidence baskets actually attract more amendments?
  5. E5Slice evaluationHow does performance change across specific categories?
  6. E6Business outcomeHow many orders were later disowned, cancelled or refunded by the shopper?

Floor — the outcome the merchant answers for

Failure modes

Where each failure originates in the agent

Seven failure modes, placed at the stage each one begins.

Agent lifecycle

Direction of processing →

  1. 01 · Retrieval

    1 mode

    • DY-03

      Superseded card value

      Price or stock read from a card already replaced.

    Stage gathers

    Catalogue, price cards, stock and configured rules

  2. 02 · Reasoning

    2 modes

    • DY-04

      Version-number inference

      A feature is read off a specification version number.

    • DY-06

      Personalised price signal

      Data about the individual reaches the price shown.

    Stage proposes

    Candidates, attributes compared and confidence

  3. 03 · Tool / write

    2 modes

    • DY-02

      Unauthorised purchase

      An order is placed without the shopper's own authorisation.

    • DY-05

      Subscription enrolled

      A trial that converts to a recurring charge is taken up.

    Stage writes

    Only where write access and approval policy allow it

  4. 04 · Output

    1 mode

    • DY-01

      Review summary drift

      A summary reads warmer than the reviews behind it.

    Stage returns

    The recommendation the shopper sees and acts on

  5. 05 · Change / Version

    1 mode

    • DY-07

      Silent disclosure loss

      A model or template change drops a required disclosure.

    Stage tracks

    Model, prompt, disclosure templates and card rules

  • Sev-1 · a purchase made without authorisation
  • Sev-2 · a wrong claim reaches the shopper
  • Sev-3 · a source degrades, basket routes to check
See the complete Electronics failure-mode catalogue

Affected slices

The average hides where this concentrates

In aggregate the disowned-order rate looks settled; by slice, a few session types carry most of it. Nestack reports the disowned-order rate by cohort, not only in total.

Slice performance — reported separately, not only in aggregate

Illustrative example
SliceFailure rateLiftLift vs. thresholdStatus
Third-party agent surfaces3.7%3.4×Review
Bundles and accessories3.1%2.8×Review
New-launch product lines2.2%2.0×Watch
Repeat reorders on file1.0%0.9×Normal

Bar: disowned-order-rate lift vs. repeat-reorder baseline · scale 0–4.0× · tick marks the 2.0× review threshold

2 of 4 slices over threshold

Evidence-linked improvement

A cycle ends with a standing test

Explaining a bad recommendation does not close the cycle. A standing regression case does, and that suite is what the next session is measured against.

Improvement cycle · five stages

Switchback — the path turns at Improve and returns at Learn

  1. 01

    Detect

    Disowned orders rise in one session slice.

  2. 02

    Diagnose

    The named commerce owner opens the sessions and the cards behind them until one cause holds.

  3. 03

    Improve

    The fix is versioned against the sessions that produced it.

  4. 04

    Verify

    The release stops until every affected case is passing.

  5. 05

    Learn

    The case stays in the suite, and the recommendation policy is amended.

  6. Learn → Detect

    The return edge. What comes next is measured against a longer suite.

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

Workstream

Week 1Week 2Week 3Week 4Week 5Week 6

  1. 01Commerce workflow discovery and boundary definition.Week 1
  2. 02Catalogue, PIM and feed source assessment.Week 1, Week 2
  3. 03Review, disclosure and price-rule configuration mapping.Week 1, Week 2
  4. 04Catalogue ingestion and normalisation.Week 2
  5. 05Ranking logic and attribute binding.Week 2, Week 3
  6. 06Confidence scoring and check routing.Week 3
  7. 07Shopper authorisation workflow.Week 3, Week 4
  8. 08Commerce-platform and payment integration.Week 5
  9. 09Authorisation-path cases.Week 4, Week 5
  10. 10Guardrails and purchase controls.Week 4
  11. 11Session-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 storefrontProductionProduction storefrontsAdvancedMultiple markets / stores
Introduced at Pilot
Ranking from your catalogue✓✓✓
Shopper authorisation✓✓✓
Recommendation-quality baseline✓✓✓
Introduced at Production
Reporting by category—✓✓
Authorisation flow in your systems—✓✓
Approved write-back—✓✓
Commerce-platform integration—✓✓
Introduced at Advanced
Multi-market disclosure sets——✓
Multi-storefront authorisation——✓
High session volume——✓
Multi-market storefront controls——✓
Build priceFrom $5,000From $8,000Custom quote
Final build price
Confirmed after discovery based on integrations, workflow complexity, session volume, authorisation 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 catalogue attributes and price-card structure

    Catalogue ingestion and attribute mapping

    Week 1

  2. 02Representative shopper sessions

    Ranking baseline, attribute binding and comparison logic

    Week 2

  3. 03Your review-handling and disclosure rules

    Review, disclosure and price-rule mapping, and the boundary

    Week 1

  4. 04Access to relevant APIs, feeds or exports

    Catalogue, PIM and commerce-platform assessment, then setup

    Week 2

  5. 05Recommendations that should not have gone out

    Authorisation cases and the evaluation suite

    Week 4

  6. 06Where a session must stop and ask the shopper

    Confidence scoring, check routing, guardrails and purchase controls

    Week 3

  7. 07A named commerce owner to sign the rules

    Shopper authorisation 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

Phases occupy the weeks the work really needs, so week 5 runs evaluation and launch side by side.

Phase

W1

W2

W3

W4

W5

W6

  1. DiscoveryW1
  2. BuildW2 – W3
  3. EvaluateW4 – W5
  4. Pilot & LaunchW5 – W6

Week focus

W1Commerce workflow discovery, rule mapping and the automation boundary

W2Catalogue integration and the ranking baseline

W3Ranking workflow, confidence logic and purchase controls

W4Evaluation suite, review and disclosure checks, and failure-mode testing

W5Payment integration, pilot sessions and targeted corrections

W6One trading period run under the commerce team, then handover

Reading the band
Each bar spans only the weeks its work is named in. The week 5 overlap is real work, not padding.
At the end of W6
The period closes validation and Agent Care picks up the monitoring.
Duration
Six-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · Electronics AI agent

Build a commerce agent around an authorisation you can produce.

Show us your catalogue, your disclosure rules and who owns them. If you cannot yet show what a shopper authorised, we start there — that question is unsettled.

Typical delivery
4–6 weeks
Deployment
Your catalogue
Shopper consent
Per-purchase
After launch
Agent Care available

Nestack Agents · Commerce and shopping

AGT-EL-06 · Agent Care available after launch

Build a commerce agent

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

About you
Your storefront

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