Sports AI agent · Ticket pricing
Dynamic-Pricing & Ticketing-Demand AI Agent
Read demand by event and tier, propose a price move inside the approved band, and hold it for the named pricing manager — who decides whether the price card changes.
- Typical delivery
- 4–6 weeks
- Deployment
- Your stack
- Manager decides
- Pre-display
- After launch
- Agent Care
What this agent does
The constraint is the display, not the move
In
- 01
Event, inventory and on-sale history ingested from supported ticketing, CRM and demand sources.
- 02
Tier names, seat attributes and fee components normalised, each carried forward with its source.
Reason
- 03
A demand read per event and tier, built from aggregate signals and never from an individual fan.
- 04
Price moves proposed inside the band, floor and jurisdiction rules configured for the venue.
- 05
Accessible seating carried as a separate class, outside dynamic hold, re-tiering and optimisation.
Decide
- 06
The all-in total re-rendered as the most prominent price on the surfaces the move reaches.
- 07
Each proposed move routed to the named pricing manager before it reaches a display.
Out
- 08
Prior total, new total, rule ID, model version, approver and surfaces retained per move.
- 09
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
- 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.
Goes to the named pricing manager to approve.
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 required
8 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 boundary
Agent 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 tier
Illustrative example- Event
- Midweek league fixture
- Proposed move
- Upper tier moved one band step on a slowing sell-through
- All-in total
- $68.00 all-in
- Source of record
- Sell-through on file
- Confidence
- 89%
- Display
- Total shown most prominently
As received
Taken 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 move
It sits inside the band and touches no accessible seat — the move the manager weighs.
What the score decides
Below the configured threshold the move picks up a display read before it reaches the manager.
Action
ApproveAmendSend to display reviewValue
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 on-sale
From the ticketing record
Read the demand on file
Draw on sell-through, comparable on-sales and the band the pricing manager configured.
Price the move, show the total
Routine tier moves arrive proposed, checked against the band and rendered all-in under 16 CFR 464.
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.
Build 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 systems
- Ticketmaster
- AXS
- SeatGeek
- Tickets.com
Distribution
- Marketplace and resale APIs
- Partner and affiliate feeds
CRM and fan data
- Salesforce
- Dynamics
- Fan data platform
Agent
Dynamic pricing and demand
- Reads the demand
- Proposes the move
- Holds for approval
Display surfaces
- Web
- app
- Paid and partner creative
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 price card
Controls nest inward. What passes through the whole stack is named in the map below.
L6 · Outermost — last line of defence
Inward → L1 · closest to the model
- L1 – L2
- Test whether a move may stand
- L3
- Puts the release in a manager's hands
- L4 – L5
- Show what the price was moved on
- L6
- Reverts 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
- 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 lifecycle
Direction of processing →
01 · Retrieval
1 mode
- TK-03
Stale inventory read
Sell-through read from a snapshot the on-sale has moved past.
Stage gathers
Event record, inventory map, sales history and band config
02 · Reasoning
2 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 proposes
Tier, prior total, proposed total and confidence
03 · Tool / write
2 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 writes
Only where write access and approval policy allow it
04 · Output
1 mode
- TK-01
Total not most prominent
A component price renders larger than the all-in total.
Stage returns
The price the buyer sees and the venue answers for
05 · Change / Version
1 mode
- TK-07
Silent band regression
A model or rule change widens the moves the agent will propose.
Stage tracks
Model, 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
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 aggregate
Illustrative example| Slice | Failure rate | Lift | Lift vs. threshold | 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 stages
Switchback — the path turns at Improve and returns at Learn
- 01
Detect
Amendment rate rises in one event slice.
- 02
Diagnose
By the second on-sale it is visible: a pricing analyst reads back through the moves and the demand each one rested on.
- 03
Improve
Each change is versioned against the price moves that exposed it.
- 04
Verify
A failing case blocks the release until it goes green.
- 05
Learn
The case is retained, and the pricing guardrails are rewritten.
Learn → Detect
The 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.Week 1
- 02Ticketing and demand-source review.Week 1, Week 2
- 03Price band, floor and jurisdiction rule-set mapping.Week 1, Week 2
- 04Event and inventory ingestion.Week 2
- 05Demand-read logic and price-move binding.Week 2, Week 3
- 06Confidence scoring and approval routing.Week 3
- 07Pricing approval workflow.Week 3, Week 4
- 08Ticketing and display-surface integration.Week 5
- 09Display and hold-release cases.Week 4, Week 5
- 10Guardrails and approval controls.Week 4
- 11Price-trail instrumentation.Week 5, Week 6
- 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 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 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.
You bring
We build with it
01Your event calendar, inventory map and tier structure
→Event and inventory ingestion and fact mapping
Week 102Representative on-sales and their sales history
→Demand-read baseline, signal binding and move logic
Week 203Your price bands, floors and fee-display rules
→Band, floor and jurisdiction-rule mapping
Week 104Access to relevant APIs, feeds or exports
→Ticketing, CRM and demand-source assessment, then integration setup
Week 205Price moves you would not want repeated
→Display cases and the evaluation suite
Week 406Where a price move must wait for approval
→Confidence scoring, approval routing, guardrails and pricing controls
Week 307Named pricing managers to approve moves
→Pricing 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
Each band covers the weeks the work really takes, so evaluation and launch share the fifth.
Phase
W1
W2
W3
W4
W5
W6
- DiscoveryW1
- BuildW2 – W3
- EvaluateW4 – W5
- Pilot & LaunchW5 – 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 band
- A bar covers only the weeks its work is named in. The week 5 overlap is real, not padding.
- At the end of W6
- The on-sale closes validation and Agent Care picks up monitoring.
- Duration
- Six-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.
- Typical delivery
- 4–6 weeks
- Deployment
- Your ticketing stack
- Manager decides
- Pre-display
- After launch
- Agent Care available
Nestack Agents · Dynamic pricing and ticketing demand
AGT-SF-10 · Agent Care available after launch