01 / Customer question
The commercial context
Protect desirability as shopping becomes more automated.
Fashion discovery depends on more than a generic product description. Current collections, occasion, fit, fabric and seller authenticity all change whether a recommendation makes sense. An answer built around a discontinued style or the wrong size variant can damage the experience.
Brands also have different expectations of access. A mass-market retailer may favour broad catalogue distribution, while a luxury house may prioritise curated discovery and clienteling. We assess the information and channels against your brand standards, full-price economics and rights in creative assets.
Customer journeys
Test style, fit and authenticity questions.
We build the assessment around specific questions, audiences and markets. These examples show the kinds of journeys we can examine; the final scope follows your priorities.
02 / Customer question
Is the correct size/colour variant recommended using reliable fit and fabric information?
03 / Customer question
Can the shopper distinguish the authentic product, current collection and approved seller?
How SWLR can help
Make collections understandable and representation consistent.
01
Collection and brand evaluation
We evaluate occasion and style questions against current collections, selected markets and approved channels. The findings distinguish discovery gaps from incorrect product or brand representation.
You receive: Collection visibility and brand-language findings.
02
Product and visual information
We assess style, colour and size relationships, fit systems, fabric and care information, and image metadata. The priorities address product matching and the information required for useful visual or conversational discovery.
You receive: Variant/fit data priorities and visual-discovery evaluation.
03
Creative access and service pilots
We map permitted use of creative assets and scope styling or clienteling assistance with brand owners. Pilot criteria cover accuracy, language, authenticity and the points where a person should take over.
You receive: Asset access policy options and a brand-reviewed pilot brief.
Internal AI readiness
Give merchandising and clienteling teams usable, approved knowledge.
Collection releases, product updates and creative approvals need clear ownership across merchandising, ecommerce and brand teams. We assess the knowledge available to colleagues and the workflow needed to keep it current.
Styling and clienteling pilots should use approved product information and respect CRM permissions. Generated language or imagery needs review against your standards. The scope preserves the role of human judgement in personal service, especially where authenticity, fit or provenance is uncertain.
A practical first engagement
Fashion AI Discovery & Brand Assessment
We agree the brands, market, current collection, representative styles and variants, approved sellers and asset rights. You receive discovery findings, brand and fit errors, creative-access options and a prioritised collection-data roadmap, with a defined scope for any service pilot.
01
Agree the scope
We define the business questions, references, AI surfaces and teams involved. Access requirements and dependencies are agreed before the assessment begins.
02
Review the evidence together
Findings distinguish observed answer behaviour from the underlying content, data or workflow issue. Your teams help establish which changes are material and feasible.
03
Choose the next action
The roadmap sets out priorities, owners, dependencies and validation. Where a pilot makes sense, we scope the implementation and evaluation work with the relevant teams.
Evaluation
Measure the changes that matter.
We agree the criteria before making changes. Answer samples are recorded with their questions, market, surface and date. Repeat checks help show patterns within that scope; commercial outcomes and internal workflow gains need their own evaluation with your teams.
Current-collection presence
Fit and variant accuracy
Authentic seller representation
Full-price conversion
Part of Ayima
Technical search expertise. Practical enterprise thinking.
SWLR brings an AI visibility and readiness remit to Ayima's enterprise search background. We connect the business question to the content, data, access and technical work behind it, then help teams prioritise the next steps.
Common questions
Before we begin.
Should luxury brands expose their full catalogue?
That depends on the brand, collection and channel strategy. Accurate approved product information can support discovery without granting unrestricted use of every asset. We assess curated and broader access options against the desired customer experience.
Can we protect images while supporting discovery?
Access decisions can differ by purpose and asset. Product discovery, image reuse and model training do not have to share one policy. Controls and rights terms have practical limits, which should be understood before choosing a route.
Can AI improve fit recommendations?
It may help where size systems, measurements and product information are reliable. We first evaluate the data and relevant scenarios. A pilot needs fit-quality and returns measures rather than an assumption that automation will reduce returns.
Signal → Evidence → Action
Start with the questions that matter.
Discuss your collections, discovery channels and the brand standards the work needs to preserve.