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Running From idea to settled cost Schedule on time Machines up Modeler · PLM + pre-planning
Modeler
AI-native platform for the fashion industry

From idea to market, in a single thread.

Modeler is not just another PLM. It is the platform that decides what to produce — and carries that decision to the shop floor. An AI brain at every step, and a team of specialists working for you.

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Operations dashboardAurora Lingerie · Example
In development
184
Styles in the collection
Settled cost
71%
131 of 184
Overdue stages
12
Across 4 areas
Machines down
6
2 waiting for a part
Schedule · High SummerWK 32 → 38
Design
Pattern making
Sample
Approval
Cutting
Your AI team

Not features with AI. A team of AI employees.

Your team prepares. You decide. Everything signed and explainable.

Mia understands your request, assembles the right team and returns a single answer. Tap whoever you want to meet.

Squads — Mia gathers the team for a process
Tap a squad to see who takes the field.
The whole product, in four movements

One system, from design to shop-floor reporting.

Each front has its modules — and the AI specialist who lives there.

01Create

Create and specify

From the idea to a technical drawing ready to produce — the tech pack filling itself in from what already exists.

Creative StudioCollectionsTech packPattern making / CADColours & printsMaterials
Roles: Designer e Pattern maker
02Decide

Cost and decide

Should this style be launched, and in what volume? Cost, price, demand and risk on the same screen.

CostsPricingDemandMarketApproval board
Roles: Cost analyst e Salesperson
03Produce

Plan and produce

The decision becomes an order: real capacity, contractors end to end, shop-floor reporting.

TimelineCapacity (APS)Shop floor (MES)ContractorsPurchasing
Roles: Planner, Floor supervisor e Buyer
04Measure

Measure and learn

Real time per operation, defects at the source, sales — everything comes back and sharpens the next decision.

Time studyQualityMaintenanceIndicatorsCompensationERP integration
Roles: Inspector, Analyst e Mechanic
The modules · the story of a style

Twenty-two modules, told in the order a style lives.

Turquoise marks where the AI steps in — and where someone signs afterwards.

Follow the thread. Each chapter is a stage in the life of a style; each module is what Modeler does for it there — and the AI specialist who lives there.

  1. Chapter 01 · Create

    The idea

    Every style starts as a sketch, a photo, a sentence. Here it gets a name, a reference and the two answers that avoid an expensive collection: have we made this before? is it worth it?

    On the field
    Designer

    Creative Studio

    The idea before there is a style.
    • A guided interview turns the sketch into a brief, with feasibility read before it becomes a tech packAI
    • Moodboard and board generated in the studio itself; the style on a mannequin from your sketchAI
    • Side-by-side comparison: two ideas or two versions, on the same screen, for the decision

    Collections

    The whole line plan on one screen.
    • Planned × actual mix, article by article, with stage and owner
    • Price pyramid with your brand's target band — the AI classifies the style from the sketchAI
    • Visual map: the whole collection in sketches, for the table to look at together

    Prints

    From the archive to the style, with licence and colour.
    • Print with family, technique, supplier and colourways; files per variant
    • Licence with validity: the style knows which licensed print it uses
    • Colour read from the sketch and matched to the company's colour chartAI
  2. Chapter 02 · Specify

    The style takes shape

    The drawing becomes a tech pack: parts, measurements, materials, consumption. It is the most important record in the system — and it fills itself in from what already exists before asking anyone to type.

    On the field
    Pattern makerBuyer

    Styles

    The tech pack, alive.
    • Materials per part and per colour, measurements with tolerance, variants with generated SKU
    • The tech pack is born classified: reference, size range and article read from the sketch — only where the reading holdsAI
    • Frozen revision with the cost of that moment; PDF tech pack per style, per batch or the whole collection book

    Pattern making

    CAD comes in without a plugin.
    • Reads the DXF and draws the pattern on screen; from the marker it takes width, length and utilisation
    • Several files at once — each finds its own style by the reference it carries
    • 3D model in the tech pack and pattern fitting with measurements checked against tolerance

    Materials

    Fabric, trims and services, with dated prices.
    • Fibre composition, supplier, swatch image; material sheet read from a photo or PDFAI
    • Prices with an effective date: yesterday's cost can still be reconstructed
    • Quotes through the supplier portal, comparing metre, kilo and piece on the same screen
  3. Chapter 03 · Decide

    The number

    Should this style be launched — and in what volume? Cost, price, demand and market at the same table. The engine calculates, the AI explains, and someone signs.

    On the field
    Cost analystSalesperson

    Costs and margins

    The cost that is never a guess.
    • Tax, freight and overhead in the engine; wholesale and retail price with target margin
    • “What if” scenario: swap material or supplier and see the effect on cost without saving to the tech pack
    • Alert for consumption outside the article's history — the AI flags what stands out, the engine recalculatesAI

    Demand

    How much to sell, before cutting.
    • Imports your sales, from a spreadsheet or the ERP, with a check before saving
    • Volume forecast per style from five signals: sales, similarity, competitor, cost and productionAI
    • Accuracy: the forecast against what sold, per style and per collection

    Approval board

    The decision, signed live.
    • Session with a stage, a queue of styles, a timer and a vote with a reason
    • Cost, market and collection diagnosis on the table, prepared by the AI teamAI
    • Live scoreboard; the approved volume is recorded with who decided
  4. Chapter 04 · Produce

    The decision becomes an order

    Approved? Now it has a date, a factory, a contractor. Does the schedule slip? The cascade warns. Does it fit the capacity? The maths answers before you promise.

    On the field
    PlannerBuyerFloor supervisor

    Timeline

    Deadlines with dependencies and a critical path.
    • Gantt that replans in cascade when a date slips; board by stage and schedule templates
    • Mia notices the delay and proposes the dates already filled in — nothing changes until you clickAI
    • Automatic, recurring opening per area; spreadsheet import with a check

    Capacity planning (APS)

    Does what I'm launching fit in the factory?
    • Work centre, shift and resource — in-house and contractor — with the capacity of the coming days
    • Load × capacity: what you intend to produce against the available minutes, in a heatmap per sector
    • Order simulation: does it fit? Yes, partially or no — with a possible date and alternatives with contractors or overtime

    Contractors

    The order end to end, even on the contractor's phone.
    • Dispatch and return with five quantities: good, seconds, scrap, rework and balance
    • Contractor portal on the phone: report production, deliver, open an incident
    • Price checked against your table; partner performance in four numbers

    Shop floor

    What actually happened, stage by stage.
    • Mirrors the order as the ERP runs it: what left each stage, what stopped and why
    • Lead time by sector, time deviation against the time-study standard, stoppages and rework per defect
    • Closes the planned × actual loop that cost and capacity need
  5. Chapter 05 · Measure

    Measure and care

    Time per operation, defects at the source, machines up and running, numbers that guide. What is measured here goes back to the start of the thread and sharpens the next decision.

    On the field
    InspectorMechanicAnalyst

    Time study

    The shop-floor stopwatch.
    • Time study per operation, with the style's routing: sector, operators, setup
    • The video measures: film with the tablet or upload the file, and mark the cycles on the timeline in slow motion
    • Standard time with its origin recorded — who measured, how and when

    Quality

    Defects at the source, not at the customer.
    • Configurable checklist per target: style, material, equipment, order
    • Mia interviews whoever will inspect and proposes the checklist item by itemAI
    • Lot inspection at the contractor, report with validity, non-conformity mode × cause

    Compensation

    The pay that comes out of the shop-floor record.
    • Policies by output, quality and attendance, simulated before they take effect
    • Settlement by person and by team, with every block spelled out
    • Mia explains every line of the settlement and every rule of the policyAI

    Maintenance

    A machine up is a style on time.
    • Preventive plan by time or by use, with a linked checklist
    • The operator opens the request in two screens; it becomes a work order in one click
    • Time between failures, repair time, backlog and preventive compliance

    Indicators

    The number that changes a decision.
    • Builder: 11 metrics × 17 dimensions, without depending on IT
    • 20 ready-made analyses and 8 dashboards organised by who asks the question
    • Compares period with period; exports to Excel and PDF with its own permission

    Reports

    The report you build yourself.
    • Pick entity, columns, filter and order; save as a template and print
    • Searchable audit trail: who changed what, from which value to which, when
    • Printed in your brand's style
  6. Chapter 06 · Sustain

    The house

    Underneath it all: the ERP talking, the team talking, and each person seeing only what they may. Mia lives here — and runs through the other five chapters.

    On the field
    IntegratorSupport agentAuditorMia

    Integrations

    The ERP still owns the order; Modeler talks to it.
    • TOTVS Moda via API, generic API and file, with a scheduler and encrypted credentials
    • Bulk import with a line-by-line check before saving
    • Mia queries external sources — exchange rates, company registry, postcodes — when the company opts inAI

    Messages

    Conversations per style, per idea, per topic.
    • Mentions, attachments, photos and read receipts, in real time
    • Bell at the top, browser push with the system closed, e-mail that insists
    • The reply stays attached to what it answers — never in a separate app

    Administration

    Each person sees what they may. The company, with your brand.
    • Module × action permissions, groups and cloning between groups
    • Two-step verification; a provisional password on paper for those without e-mail
    • Your brand on every screen, four languages, privacy and data protection by default
22
Modules that talk to each other
14
AI employees on your team
6
Squads ready for a process
0
Decisions taken without your signature
Your team prepares. You decide. Subscribe to the chapters your operation already lives — the others wait on the same thread.
What we are now

The platform that decides what to produce — and carries the decision all the way to the sewing line.

Built for fashion, the way fashion works. An AI team that prepares; the decision is always yours.

Try for free I already have an account