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For agencies & consultants

Scale trend work across every account, every season

Compress the research drag on every engagement. Data-driven direction across every client, every season.

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  • Collaborative workspace
  • Data-driven analysis
  • Client-ready outputs
J. Salinas · FW26 · Look 30

J. Salinas · FW26

Pantone

Kelly Green

16-6138 TCX

— On agencies and consultants

"Agencies should spend less time rebuilding research, and more time shaping client direction."

01 — The pattern

Where agencies and consultants lose time

  • Every brief starts from scratch

    New client projects often repeat the same runway research, reference gathering, and deck-building work.

  • Evidence clients can trust

    Client recommendations need clear data behind the colors, silhouettes, categories, and pattern you present.

  • Per-client workspaces

    Separate references, boards, trend signals, and outputs by client, season, and project.

  • Too many disconnected tools

    Data, references, moodboards, and AI outputs often live in separate places, slowing down every client deliverable.

02 — The workflow

From source to action, four steps

The same workflow runs across every team. The artifacts and language change with the role.

  1. 01

    Read the signal

    Capture runway, presentation, and street-level signal at the silhouette, color, fabric, print, and category level.

  2. 02

    Find the references

    Search by theme, visual similarity, or natural language to connect emerging directions with relevant looks, details, and design references.

  3. 03

    Generate direction

    Turn signal and references into AI-assisted concept variants grounded in real fashion structure.

  4. 04

    Align the team

    Pull everything into shared moodboards, comments, and exports the team and stakeholders can act on.

03 — Sample outputs

What fashion brands can act on

  • Faster client approvals

    Support every recommendation with runway-backed data, helping client teams review, align, and approve decisions faster.

  • Brand-fit moodboards

    Create moodboards tailored to each client’s brand codes, category focus, and visual direction.

  • AI-assisted concept variants

    Generate desgin directions and visual variants grounded in data, client context, and fashion-native inputs.

  • Per-client workspaces

    Keep each client’s references, boards, trend signals, AI outputs, and deliverables organized in one workspace.

  • Client-fit inspiration search

    Search runway looks by theme, silhouette, color, or product detail to build inspiration tailored to each client’s brand identity.

04 — Use cases

Where runway intelligence supports your week

Use runway-backed insights across collection, buying, merchandising, campaign, and leadership conversations — without rebuilding the same research each time.

  • 01

    Client onboarding research

    Start each new client brief with runway-backed signals, references, and category context instead of rebuilding research from zero.

  • 02

    Seasonal advisory retainers

    Deliver recurring Fashion Week and category readouts for multiple clients from one organized workflow.

  • 03

    Client-fit inspiration search

    Use thematic and visual search to find runway references aligned with each client’s brand identity and creative direction.

  • 04

    AI visual variants

    Create image variations in seconds with color, fabric, pattern, and styling changes using AI studio.

  • 05

    Faster Approvals

    Support recommendations with runway-backed data so client teams can review, align, and approve decisions faster.

  • 06

    All in one workspace

    Keep runway data, runway archive, AI generated visuals and moodboards in one organized fashion workspace.

— Methodology

Data-driven, fashion-native, collaborative

  1. 01

    Thousands of runway looks are structured into garment-level data, with every signal linked back to its show, season, designer, and image.

  2. 02

    Pattern recognition, not guesswork. T-Fashion compares signals across seasons, designers, categories, colors, fabrics, and silhouettes to show what is gaining or losing momentum.

  3. 03

    Fashion-native language. Each look is broken down into fashion attributes from category, silhouette, fabric, pattern, and motif to 2,400+ Pantone TCX color mappings.

  4. 04

    Collaborative decision layer. Teams work from the same layer of data, references, boards, and AI outputs without losing context.

FAQ

Common questions

How does T-Fashion fit into agency engagements?

Agencies use T-Fashion to compress research, build client-ready boards and decks, and ground AI concept work in real fashion signal - across multiple accounts.

Can we keep client work separate?

Yes. Workspaces support per-account projects with shared references, comments, and version history scoped to each client.

Can we present T-Fashion outputs directly to clients?

Yes. Boards and decks export with full reference attribution, suitable for client-side reviews and stakeholder meetings.

Is this an alternative to our trend subscriptions?

For many agencies, yes. T-Fashion combines signal capture, visual reference, and concept generation in one workflow - replacing stitched-together trend reports and image research.

Does it support sourcing-side advisory work?

Yes. Sourcing firms and consultants use T-Fashion to align factories, buyers, and trend direction with structured runway and market signal.

Other teams

Same workflow, different lens

Get started

See it on a client account

Bring a client engagement, a pitch, or a season ask. We will run a sample analysis and walk through how agencies use T-Fashion across accounts.

Request client-ready sample → See AI Studio →