Dynamic-Pricing & Ticketing-Demand AI Agent

What this agent does

The constraint is the display, not the move

Event, inventory and on-sale history ingested from supported ticketing, CRM and demand sources.

Tier names, seat attributes and fee components normalised, each carried forward with its source.

Reason

A demand read per event and tier, built from aggregate signals and never from an individual fan.

Price moves proposed inside the band, floor and jurisdiction rules configured for the venue.

Accessible seating carried as a separate class, outside dynamic hold, re-tiering and optimisation.

Decide

The all-in total re-rendered as the most prominent price on the surfaces the move reaches.

Each proposed move routed to the named pricing manager before it reaches a display.

Out

Prior total, new total, rule ID, model version, approver and surfaces retained per move.

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

→ Product statement

The agent proposes the move; the named pricing manager decides what is published, and the venue stays the seller of record.

Example workflow

One event, demand read to on-sale

AgentHuman

1On-sale event receivedTicketing system, inventory map, sales history or demand feed

2Demand readSell-through, time-to-event, opponent, day-of-week and comparable on-sales, each with its source

3Move proposedTier, prior total, proposed total, flagged surfaces and confidence

4Controls appliedBand and floor checks, the §36.302(f) accessible carve-out, jurisdiction rules and confidence threshold

No human action required

Stages 1 to 4 run unaided, and no price moves at any of them — the agent is proposing, and the manager's lane opens at the confidence gate.

5DecisionBranches at the confidence threshold

High confidence

Goes to the named pricing manager to approve.

Low confidence

Adds a display-compliance read first.

Pricing approval

The move is held with its demand read, its flagged surfaces and the confidence.

Approve · Amend · Send to display review

Approved — released to the price card▼

6Ticketing systems updatedOnly where write access and approval policy allow it

7Outcome evaluatedForecast error, amended moves, total-rendering checks and corrections made after a price went live

Amendments

Every manager amendment is counted in the evaluation.

What should not run autonomously

Human approval stays in control

Outside the boundary — human approval required8 items

Any move to accessible-seating price, tier or hold.

A total outside the band the pricing manager approved.

Changing how the all-in total or a fee is displayed.

Pricing from an identified individual's personal data.

Automation boundaryAgent acts unaided

✓Read demand for an on-sale from aggregate event signals for the named owner.

✓Propose a price move inside the approved band.

✓Render the all-in total on the surfaces it writes.

✓Release general inventory within the hold policy on file, and hold the rest.

Any price move runs inside the boundaries agreed at implementation, never ahead of approval.

Listing inventory the client does not yet hold.

Sharing one demand engine with a competing seller.

Managing buyer accounts, queues or purchase limits.

Changes to band, display or hold-release rules.

Example output

One price move, annotated

Everything the agent proposes is attached to the demand read it came from.

Price-move output · single event tierIllustrative example

Event

Proposed move

All-in total

Source of record

Confidence

Display

Midweek league fixture

Upper tier moved one band step on a slowing sell-through

$68.00 all-in

Sell-through on file

89%

Total shown most prominently

As receivedTaken from the ticketing record and the sales history on file — nothing here is set by the agent.

Demand evidence used Sell-through to date Comparable on-sales Time-to-event curve

Why this moveIt sits inside the band and touches no accessible seat — the move the manager weighs.

ActionApproveAmendSend to display review

What the score decidesBelow the configured threshold the move picks up a display read before it reaches the manager.

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 on-saleFrom the ticketing record

03Pricing

Read the demand on file

Draw on sell-through, comparable on-sales and the band the pricing manager configured.

01Approved path

Price the move, show the total

Routine tier moves arrive proposed, checked against the band and rendered all-in under 16 CFR 464.

02Human review

Send review to the moves

Moves at the band edge, on a regulated surface or near a held class are marked, so the manager reads those first.

04Build an evidence trail

The price, the demand read behind it and the approval that released it stay on the event record.

Integrations

Typical integrations

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

Ticketing systemsTicketmaster · AXS
SeatGeek · Tickets.com

DistributionMarketplace and resale APIs
Partner and affiliate feeds

CRM and fan dataSalesforce · Dynamics
Fan data platform

Agent

Dynamic pricing and demand

Reads the demand
Proposes the move
Holds for approval

Display surfacesWeb · app · email
Paid and partner creative

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 price card

Controls nest inward. What passes through the whole stack is named in the map below.

L6 · Outermost — last line of defenceInward → L1 · closest to the model

L6Rollback / safe modePull pricing back to demand-read-only when evaluation or production signals degrade.Roll back

L5Version monitoringTrack model, prompt, band-configuration and jurisdiction-rule changes.Track

L4TraceabilityRecord the prior total, the new total, the rule ID, the approver and the surfaces.Record

L3Pricing approvalHold moves for the named manager; it governs release, not whether an approved price is right.Gate

L2Policy guardrailsTest each move against band, floor, accessible-class and total-rendering rules; a failure returns it.Restrict

L1Confidence thresholdsRoute low-confidence moves to a display read before the manager sees them.Require review

Model coreMove proposed — tier, prior total, proposed total, flagged surfaces and confidence

L1 – L2Test whether a move may stand

L3Puts the release in a manager's hands

L4 – L5Show what the price was moved on

L6Reverts to the published price card when signals degrade

How Nestack evaluates it

Evaluate the pricing workflow — not only the number that shipped.

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

Surface — the price the buyer sees

Depth of coverage ▼

E1Final-output evaluationDid the all-in total render as the most prominent price on each surface tested?

E2Step-level evaluationDid the agent use the right event, band and jurisdiction configuration?

E3Tool evaluationDid it read and write the correct event, tier and inventory class?

E4Confidence calibrationDo low-confidence moves actually attract more manager amendments?

E5Slice evaluationHow does performance change across specific event types?

E6Business outcomeHow many moves needed an amendment or a correction after the price went live?

Floor — the exposure the venue answers for

Failure modes

Where each failure originates in the agent

Seven failure modes, set at the stage where each one begins.

Agent lifecycleDirection of processing →

01 · Retrieval1 mode

TK-03

Stale inventory read

Sell-through read from a snapshot the on-sale has moved past.

Stage gathersEvent record, inventory map, sales history and band config

02 · Reasoning2 modes

TK-04

Accessible seat re-tiered

A regulated inventory class is reasoned about as ordinary supply.

TK-06

Competitor-price inference

A move is justified from another seller's price rather than own demand.

Stage proposesTier, prior total, proposed total and confidence

03 · Tool / write2 modes

TK-02

Unrendered surface

A total publishes to a surface the display test did not cover.

TK-05

Tier moved twice

One tier takes two moves inside a single refresh.

Stage writesOnly where write access and approval policy allow it

04 · Output1 mode

TK-01

Total not most prominent

A component price renders larger than the all-in total.

Stage returnsThe price the buyer sees and the venue answers for

05 · Change / Version1 mode

TK-07

Silent band regression

A model or rule change widens the moves the agent will propose.

Stage tracksModel, prompt, band rules and jurisdiction config

Sev-1 · price published outside the boundary Sev-2 · a wrong total reaches a display Sev-3 · demand signal degrades, move routes to review

See the complete Sports failure-mode catalogue →

Affected slices

Overall pricing quality can hide one event type

Across a season the amendment rate looks small. It concentrates in first on-sales — the events with no sales history behind the demand read. Nestack reports that rate by slice, not only in total.

Slice performance — reported separately, not only in aggregateIllustrative example

Slice	Failure rate	Lift	Status
First on-sales with no history	6.4%	3.9×	Review
Accessible-seating inventory	5.1%	3.1×	Review
Events in stricter states	3.3%	2.0×	Watch
Repeat fixtures with history	1.0%	0.6×	Normal

Bar: amendment-rate lift vs. the repeat-fixture baseline · scale 0–4.0× · tick marks the 2.0× review threshold 2 of 4 slices over threshold

Evidence-linked improvement

The loop ends in the regression suite

A cycle closes on a case the next release has to pass, not on a root-cause note. That suite is what the next price move on an event is measured against.

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

01Detect

Amendment rate rises in one event slice.

02Diagnose

By the second on-sale it is visible: a pricing analyst reads back through the moves and the demand each one rested on.

03Improve

Each change is versioned against the price moves that exposed it.

04Verify

A failing case blocks the release until it goes green.

05Learn

The case is retained, and the pricing guardrails are rewritten.

Learn → DetectThe return edge. Detection next time is measured against the 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, pricing workflow, evaluation, integration, then production validation and handover.

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

01Pricing workflow discovery and boundary definition.

02Ticketing and demand-source review.

03Price band, floor and jurisdiction rule-set mapping.

04Event and inventory ingestion.

05Demand-read logic and price-move binding.

06Confidence scoring and approval routing.

07Pricing approval workflow.

08Ticketing and display-surface integration.

09Display and hold-release cases.

10Guardrails and approval controls.

11Price-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 venue, one event type ProductionProduction ticketing systems AdvancedMultiple venues / rights-holders

Introduced at Pilot

Demand read to your band and rules✓✓✓

Pricing-manager approval✓✓✓

Price-quality baseline✓✓✓

Introduced at Production

Reporting by event and tier—✓✓

Approval workflow in your systems—✓✓

Approved write-back—✓✓

Ticketing-system integration—✓✓

Introduced at Advanced

Multi-state display rules——✓

Multi-stage pricing approvals——✓

High event volume——✓

Multi-venue 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 event calendar, inventory map and tier structure → Event and inventory ingestion and fact mappingWeek 1

02Representative on-sales and their sales history → Demand-read baseline, signal binding and move logicWeek 2

03Your price bands, floors and fee-display rules → Band, floor and jurisdiction-rule mappingWeek 1

04Access to relevant APIs, feeds or exports → Ticketing, CRM and demand-source assessment, then integration setupWeek 2

05Price moves you would not want repeated → Display cases and the evaluation suiteWeek 4

06Where a price move must wait for approval → Confidence scoring, approval routing, guardrails and pricing controlsWeek 3

07Named pricing managers to approve moves → Pricing 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

Each band covers the weeks the work really takes, so evaluation and launch share the fifth.

Phase W1W2W3W4W5W6

Discovery W1

Build W2 – W3

Evaluate W4 – W5

Pilot & Launch W5 – W6

Week focus W1Pricing workflow discovery, band mapping and the automation boundary W2Ticketing integration and the demand-read baseline W3Pricing workflow, confidence logic and approval controls W4Evaluation suite, total-rendering checks and failure-mode testing W5Surface integration, pilot on-sales and targeted corrections W6One event on sale priced under the ticketing team, then handover

Reading the bandA bar covers only the weeks its work is named in. The week 5 overlap is real, not padding.

At the end of W6The on-sale closes validation and Agent Care picks up monitoring.

DurationSix-week plan shown · typical delivery 4–6 weeks depending on scope confirmed in discovery.

Next step · Sports AI agent

Build a ticketing-demand agent around the band your team already approves.

Show us your on-sale calendar, your bands and who signs a move off. You will need the fee display your surfaces render today, and the inventory map that names your accessible seating.

Discuss this agent →

Nestack Agents · Dynamic pricing and ticketing demandAGT-SF-10 · Agent Care available after launch