Zentallio

The biggest door
is not the best door.
Not for this drop.

Allocation by conversion, not store rank — so a limited release sells out where it was always going to sell.

An executive briefing

The shop floor
Illustrative · not a client store

← → to advance

SPORTSWEAR & ACTIVEWEAR · RUNNING RIGHT NOW

The AI that

Drop sell-out rate, brand-partner sell-through and full-price ratio — on one board, narrated by Iris.

Drop sell-out rate

0%

Full-price ratio

0%

Member mix

0%

Iris

Watching

LIVE · ILLUSTRATIVE DATA — hero tiles were not supplied separately for this sector; these three are taken from the sector board.

THREE THINGS A DROP CALENDAR CANNOT HOLD IN ITS HEAD

Where it clears. How many.
What the contract owes you.

Three decisions taken before a launch window opens — and all three are usually taken on store rank, gut feel and a spreadsheet.

Clearing the drop

sells out where it was always going to sell

Allocation by conversion, not store rank — so a limited release.

Iris knows which doors sell out and which sit.

Sizing the release

before the launch window opens

Pre-registration, traffic and prior drops turned into a buy quantity.

Iris reads the queue before it forms.

Reconciling the rebate

automatically, every cycle

Sell-through claims and co-op spend checked against contract terms —.

Iris reads the contract so nobody else has to.

THE BOARD · FOUR LENSES, LIVE · KINETIC · 92 DOORS · DROP SEASON

Every door
on one board.

LIVE · FRIDAY DROP · OVER-ALLOCATED TO 2 FLAGSHIP DOORS

Financial

on plan

46.2%

Gross margin · drop season

FULL-PRICE RATIO 82%

Customer

▲ 6 pts

61%

Member mix of sales

RE-ORDER RATE 34%

Operational

at target

89.3%

Drop sell-out rate

LAUNCH SLA 97%

AI-Learning

▲ improving

93.1%

Release demand accuracy

MODELS LIVE 8

LIVE · ILLUSTRATIVE DATA — Kinetic is a demonstration brand, not a deployed client. Every rule on this board is clear; the flag came from the allocation model underneath it, which is the point of the next slide.

THE SAME BOARD, THREE LAYERS DEEP

Rules fire. Models predict.
Iris explains.

L1 · Zen Rules — deterministic thresholds Rule
RuleThresholdNowState
Gross margin · drop season≥ 43%46.2%clear
Member mix of sales≥ 57%61%clear
Drop sell-out rate≥ 85%89.3%clear
Release demand accuracy≥ 89%93.1%clear

L2 · Zen Models — what is predicted

ModelPredictsAccuracy
Release demanddrop sell-out93.6%
Allocation fitconversion by door92.0%
Re-order cyclereplacement timing89.8%
L3 · Ask Iris — the same board, in words What just

What just moved?

Allocation rule flagged — two doors hold 41% of units on 18% of conversion.

Why, and what do I do?

Reallocate 140 pairs — clears the drop inside 48 hours.

This is the sector where all four rules read clear and the business still has a problem. Every threshold is green; the allocation model is the layer that can see two doors holding 41% of the units on 18% of the conversion. Iris then converts that into the only sentence that matters on a Friday — move 140 pairs, and the drop clears inside forty-eight hours.

SEVEN LIVE PRODUCTS · RUNNING RIGHT NOW

Pick one. It opens
the real screen.

Drop sell-out rate, brand-partner sell-through and full-price ratio.

Balanced Scorecard

FOUR LENSES, LIVE

Point of Sale

LIVE TILL, IRIS UPSELL

Numerus · CFO

BALANCED, NOT ESTIMATED

Nexus · Supply Chain

FORECAST, PROCUREMENT, LOGISTICS

Motus · Operations

STANDARDS, ASSETS, ENERGY

Manus · Workforce

ROSTER, PAYROLL, COMPLIANCE

Zentallio Vision

FOOTFALL, QUEUES, SAFETY

LIVE TILL, IRIS UPSELL

Point of Sale

On a drop Friday the till is the launch. A queue, a per-customer limit, a membership check and a stock pool shared with the app — all of it resolved in the seconds a customer is at the counter.

The member is recognised, not asked.

With 61% of sales going to members, membership is the default path through the till rather than a question at the end of it.

Launch rules are enforced at the counter.

Per-customer limits and release timing apply as rules, so a launch is governed rather than policed.

Iris knows what completes the kit.

The upsell is the technical layer that belongs with what is already in the basket, not a generic accessory prompt.

61%

Member mix of sales

12

Core POS solutions, standard

LIVE TILL · IRIS UPSELL

FOUR LENSES, LIVE

Balanced Scorecard

Drop-season margin, member mix, sell-out rate and release demand accuracy on one live board — with Iris naming the doors that are holding units they will not convert.

Margin is read against full-price ratio.

46.2% at 82% full price is a different business from the same margin bought with markdown, and the board shows both together.

Every rule green is not the same as nothing wrong.

This board is entirely clear while a drop is mis-allocated — which is exactly why the model layer exists underneath it.

The fourth lens audits the AI.

Release demand accuracy sits beside margin, because a buy quantity is only worth what the model behind it is worth.

89.3%

Drop sell-out rate

93.1%

Release demand accuracy

FINANCE · L2

BALANCED, NOT ESTIMATED

Numerus · CFO

Trial balance, P&L, balance sheet and cash flow on a ledger that ties out to the penny — with brand-partner rebates carried as the receivable they are rather than as a hoped-for credit note.

A rebate is a receivable, not a surprise.

Sell-through claims and co-op spend are accrued against contract terms as they are earned, not discovered at the end of a cycle.

Drop season is a working-capital shape.

A limited release is paid for long before it trades and cleared in days, and the ledger shows that rhythm rather than a monthly average of it.

Ask Iris for any number.

Any door, any drop, any partner, any period — answered in the conversation rather than a week after close.

92

Doors on one ledger

82%

Full-price ratio

FINANCE

FORECAST, PROCUREMENT, LOGISTICS

Nexus · Supply Chain

A drop is a supply chain problem with a publicised start time. The quantity is fixed before the window opens, and after that the only lever left is where the units are standing.

The buy quantity is modelled, not negotiated.

Pre-registration, traffic and prior drops give a number before the launch window opens, which is the last moment it can still change.

Allocation is the second buy.

Once the quantity is locked, putting 900 units in the wrong 92 doors costs exactly as much as buying the wrong quantity.

Inter-door movement is costed, not assumed.

Iris prices a 140-pair reallocation against leaving it and marking down, so the move is chosen on numbers.

93.6%

Release demand accuracy

48 h

Clearance window

SUPPLY CHAIN

STANDARDS, ASSETS, ENERGY

Motus · Operations

Launch execution across 92 doors, run to a standard rather than to whoever opened the store that morning — because a 97% launch SLA is an operating discipline, not a description.

A launch is a checklist with a clock on it.

Floor set, queue plan, stock staged and till rules live — verified before the window, not reported after it.

Launch SLA is measured per door.

A group number of 97% hides which three doors were late, and the three doors are the only actionable part of it.

Iris watches the exception, not the routine.

The doors that opened to standard stay quiet; the ones that did not are named.

97%

Launch SLA

92

Doors to one standard

OPERATIONS

ROSTER, PAYROLL, COMPLIANCE

Manus · Workforce

The roster built against the drop calendar — because a launch morning at a streetwear door and an ordinary Tuesday at the same door are not the same shift.

Cover follows the drop, not the week.

The doors that will clear their allocation in hours are the doors that need the staffing, and they are known before Friday.

Technical selling is a skill on the roster.

Fit and product knowledge is what converts a compression base layer, and the schedule can treat it as a named capability.

Hours, payroll and compliance on one record.

Who worked, where, at what rate — without a second spreadsheet running alongside the season.

By drop

Cover booked, not by week

92

Doors, one roster

WORKFORCE

EVERY SOLUTION · SPORTSWEAR & ACTIVEWEAR

Every solution,
on the real screen.

Grouped by what they act on. Pick one and it runs.

The launch · 3 solutions — what is releasing, and
The launch · 3 solutions — what is releasing, and where it clears

Thresholds that fire on the shift the breach happens — no model lag, no waiting for a report.

Technical size & fit guidance

L1 · SIGNAL GRID

Team & club bulk orders

L1 · LIVE QUEUE

Brand-partner rebate reconciliation

L1 · SIGNAL GRID

The season · 3 solutions — what the buy should have
The season · 3 solutions — what the buy should have been

Modelled early enough to act on, with the cause named and the move costed.

Drop & launch allocation

L2 · ROUTING

Limited-release demand modelling

L2 · MODEL TRACE

Training-cycle re-order prediction

L2 · MODEL TRACE

Plus 12 core POS solutions, standard across every Zentallio retail sector — detailed later in this briefing.

L1

Iris · Intelligence layer 01

How Iris enforces the rules.

Thresholds that fire on the shift the breach happens (the “Zen Rules” layer) — the fit guidance, the club order and the partner contract. Three solutions run on this layer.

THIS PERIOD

RULE FIRED

Return rate above target

16.8% against a 14% target, and 58% of those returns cite fit. Compression base layer is the worst line on the floor at 31% — and it is the one silhouette with no size guidance at all.

IRIS · L1 COMPRESSION

Iris · L1 · Zen Rules 01 / 03

Technical size & fit guidance

Assortment / Technical size & fit guidance  ·  Kinetic

LIVE · ILLUSTRATIVE DATA

16.8%

return rate

vs 14% target

58%

cite fit

of returns

31%

compression

worst silhouette

−4.2 pts

return rate

where guidance shown

Returns by silhouette · this period

SilhouetteReturnedFit citedGuidanceState
Compression base layer31%78%nono guidance
Technical shell19%54%nono guidance
Studio legging12%41%yesguided
Club kit8%22%yesguided
Other lines15%—partialpartial

Does guidance work? — with vs without

10.1% return rate

Guided silhouettes

24.6%

Un-guided silhouettes

31% of returns

Guided · fit cited

69%

Un-guided · fit cited

Guidance halves the return rate where it exists

Iris · what to do

The evidence is already in your own data — silhouettes with fit guidance return at 10.1%, those without at 24.6%. Compression is the worst line you sell and has no guidance at all. This is not a modelling problem; it is two silhouettes missing a rule.

Publish compression rule Add shell guidance Show return delta

Iris · L1 · Zen Rules 02 / 03

Team & club bulk orders

A club order is forty people, one deadline and a size list that arrives incomplete. It is not a large retail sale — it is a small manufacturing job that happens to be taken at a counter.

01

The order is a roster, not a basket — names, sizes, numbers and personalisation held per member rather than as a quantity by size.

02

Missing sizes are the default state of a club order, so the queue tracks what is outstanding instead of waiting for a complete list to start.

03

Personalisation and decoration are stages with their own lead times, and the promised date is quoted against them rather than against stock availability.

04

Club stock is ring-fenced from the retail pool, because a drop Friday must not consume the kit a team has already paid a deposit on.

05

Re-orders through the season are the point of the relationship, and the roster is what makes the second order take minutes rather than weeks.

L1 · LIVE QUEUE

A roster

Not a basket

Ring-fenced

Club stock, from retail

Group — The launch · “What is releasing, and where it clears.”

Iris · L1 · Zen Rules 03 / 03

Brand-partner rebate reconciliation

Sell-through claims and co-op spend checked against contract terms — automatically, every cycle. In a multi-brand sportswear business this is real money that is routinely left on the table because checking it by hand costs more than the error.

01

Contract terms are held as rules — tiers, thresholds, qualifying lines and claim windows — rather than as a PDF somebody remembers.

02

Sell-through is claimed from the same ledger that recorded the sale, so the number in the claim and the number in the accounts are one number.

03

Co-op marketing spend is matched to the activity it was granted for, which is the part most often unclaimed because nobody can evidence it later.

04

Every cycle is reconciled automatically, so a shortfall is a query raised inside the window rather than a write-off discovered after it.

05

The rebate is carried on the balance sheet as it is earned, which is what makes drop-season margin at 46.2% a real number rather than a provisional one.

L1 · SIGNAL GRID

Every cycle

Reconciled automatically

Contract

Held as rules, not a PDF

Group — The launch · “What is releasing, and where it clears.”

L2

Iris · Intelligence layer 02

How Iris predicts the drop.

What the buy should have been (the “Zen Models” layer) — modelled early enough to act on, with the cause named and the move costed. Three solutions run on this layer.

Friday drop — share of units vs share of conversion

Units Conversion

2 flagship  ·  4 streetwear  ·  other 86

Iris · L2 · Zen Models 01 / 03

Drop & launch allocation

Allocation / Drop & launch allocation  ·  Kinetic

LIVE · ILLUSTRATIVE DATA

89.3%

projected sell-out

+11 pts

140

pairs to move

2 doors

92

doors

group

48 h

clearance window

friday drop

Allocation vs conversion · Friday drop Door
DoorAllocatedConv.Will clearState
Westfield White City1800.9%62%over-allocated
Trafford Centre1601.1%71%over-allocated
Shoreditch404.2%100%under-fed
Camden Lock403.8%100%under-fed
Other 88 doors4801.8%88%sized
41% of units

Where the units are against where they sell

2 flagship doors

… on 18% of conversion

4 streetwear doors 9% of units

… on 31% of conversion

Other 86 doors 50% of units

… on 51% of conversion

The two biggest doors convert worst on this product

Iris · what to do

The drop is allocated by store size, not by who buys this product. Westfield and Trafford hold 41% of the units on 18% of the conversion, while Shoreditch and Camden will clear everything they are given in hours. Moving 140 pairs to the four streetwear doors lifts sell-out to 89% inside 48 hours.

Move 140 pairs Show conversion by door Re-run allocation

Iris · L2 · Zen Models 02 / 03

Limited-release demand modelling

Pre-registration, traffic and prior drops turned into a buy quantity before the launch window opens. A limited release has one number to get right and no second chance to get it right.

01

Demand is modelled at 93.6% accuracy from signals that exist before the launch — registrations, traffic and the shape of comparable prior drops.

02

Under-buying a release and over-buying it fail differently. One costs the margin you never made; the other costs the margin you had and marked down.

03

The queue is a forecast input, not a marketing photograph — pre-registration is the earliest honest read on how many people intend to buy.

04

Scarcity is a deliberate setting rather than an accident of buying, which is the difference between a sell-out and a stock-out.

05

Every drop scores itself against its own forecast, which is why release demand accuracy is reported on the board at 93.1% and improving.

L2 · MODEL TRACE

93.6%

Release demand accuracy

Before

The window opens

Group — The season · “What the buy should have been.”

Iris · L2 · Zen Models 03 / 03

Training-cycle re-order prediction

Performance product wears out on a schedule set by how hard it is used. A runner covering sixty miles a week replaces shoes on a calendar; the retailer who knows that calendar owns the re-order.

01

Replacement timing is modelled per customer at 89.8% accuracy, from what they bought and how they train — not from a fixed number of months.

02

Re-order rate at 34% is the number this model exists to move, and it is reported on the board beside member mix rather than buried in CRM.

03

Member mix at 61% is what makes the model possible at all — a known customer has a training history; an anonymous basket does not.

04

The prompt lands in the window before the shoe is worn out, which is the only window in which the sale is still available to you.

05

Predicted re-orders feed the buy as base demand, so replacement volume is planned rather than left to arrive on its own.

L2 · MODEL TRACE

89.8%

Replacement-timing accuracy

34%

Re-order rate, live

Group — The season · “What the buy should have been.”

L3

Iris · Intelligence layer 03 — live

Ask Iris · the drop

Not a screenshot — the actual agent, reading the same drop board the rules and models write to.

ASK IRIS — SPORTSWEAR & ACTIVEWEAR

Live Balanced Scorecard

0%

Drop sell-out rate

0%

Gross margin, drop season

0%

Member mix of sales

0%

Release demand accuracy ▲

No solution in this sector is filed under L3, because none needs to be — Iris queries all six, plus the twelve core POS solutions, in the same conversation.

STANDARD ACROSS ALL NINE RETAIL SECTORS

Twelve core POS solutions,
in every sector.

The sector solutions sit on top of these. They are not an upsell and they are not configured per customer — every Zentallio retail deployment ships with all twelve.

Checkout

Returns & exchange

Store credit

Tender & reconciliation

Tax

Discount governance

Customer capture

Loyalty

Offline resilience

Cash management

Shift close

Audit trail

HOW IT'S IMPLEMENTED

Implementation,
run by Iris.

You configure a sector playbook, not a custom project. Iris applies it herself — agentically, from day one.

Onboarding is agentic.

Iris connects the door list, the drop calendar and the brand-partner contracts directly — no manual data mapping.

Prior drops are imported, not retyped.

Historic release performance by door carries in, which is what makes allocation useful on the first Friday rather than the tenth.

Live in weeks, learning from day one.

Go-live is a configuration, not a project plan — and the next drop date is already published.

HOW SUPPORT WORKS

Support starts
with Iris.

The first line of support is agentic — Iris resolves most of it herself. Our engineers pick up from there.

Layer 1 — Iris, 24/7.

Configuration questions, anomalies and routine issues resolved directly, instantly — including through a launch window.

Layer 2 — our engineers.

Anything Iris can't close escalates automatically to a Zentallio engineer.

No blank tickets.

Every escalation arrives with Iris's own diagnosis — engineers start from an answer.

WHAT AN OPERATOR CAN EXPECT

The drop, cleared.

Units land
where they convert

Not where the door is biggest

A flag while
every rule is green

The model sees what thresholds cannot

The fit problem
named as a rule

Not as a returns statistic

The rebate claimed
inside the window

Not written off after it

Modelled outcome figures for this sector were not included in the source page. When supplied they replace these four cards and carry the standard disclaimer: modelled from pilot assumptions & comparable benchmarks — not yet a deployed-client result. All screen data in this briefing is labelled live & illustrative.

WHERE IT LEAKS, HOW IRIS RESPONDS

Where a sell-out
quietly becomes a markdown.

Where it breaks 01 A drop allocated by store rank,
01

A drop allocated by store rank, so the two biggest doors take 41% of the units and convert worst on the product.

02

A 16.8% return rate treated as a returns problem, when 58% of it cites fit and two silhouettes simply have no guidance.

03

Rebate money left unclaimed because reconciling the contract by hand costs more than the shortfall it would find.

How Iris responds L1 Fit guidance published as a
L1

Fit guidance published as a rule per silhouette, club stock ring-fenced from retail, and contract terms enforced every cycle.

L2

Release demand at 93.6%, conversion by door at 92.0%, replacement timing at 89.8% — so the cause is named, not guessed.

L3

“Why, and what do I do?” — move 140 pairs, and the drop clears inside forty-eight hours.

41% / 18%

of the units against the conversion, held by two doors — found while every rule on the board read clear, and cleared by moving 140 pairs.

ONE PLATFORM, TWO LINES

The same spine,
a different floor.

Sportswear & Activewear is sector four of nine in Fashion Retail. The layers, the seven products and Iris herself are the same ones running across ten Food & Beverage sectors.

Fashion Retail — 9 sectors

01 Apparel & RTW 02 Ethnic & Bridal 03 Kids & Teen 04 Sportswear 05 Footwear 06 Cosmetics 07 Fabric & Textile 08 Home Textiles 09 Marketplace

Food & Beverage — 10 sectors, 149 solutions

01 Quick Service 02 Casual Dining 03 Fine Dining 04 Café & Bakery 05 Ice Cream & Desserts 06 Beverages & Drinks 07 Health & Wellness 08 Cloud Kitchen 09 Institutional & B2B 10 Niche & Experience

Let's put Iris
on your next drop.

Book a call with our consultant — a pilot walkthrough on your own door list, your own release calendar.

INFO@ZENTALLIO.COM

+92 327 000 0901  ·  +1 929 419 2694  ·  zentallio.com  ·  142-C, D.H.A. Commercial Broadway, DHA Phase 8, Lahore 54940

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