Six tools that don't know what the other five decided.
Refabric is an all-in-one AI fashion tool that helps brands, retailers, and manufacturers design garments, generate automated tech packs, and produce AI product photography. A trend subscription, a design generator, a tech pack tool, a photography vendor, and a person moving files between them. Every boundary loses the brief: the Brand DNA stays in one tool, the fabric composition never reaches the pack, nobody can see how a construction change moved the cost. Refabric's agentic workflows carry the brief, the material choices and the commercial targets between stages, with human review at each one.
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Side by side
Refabric vs the four-tool stack
| Capability | Refabric | the four-tool stack |
|---|---|---|
| Scope | Trend analysis, collection development, design and variation, fabric and print, technical specs with pattern blocks and 3D, costing, manufacturability checks, AI models, photoshoots and campaign imagery | Each vendor owns one stage and exports a file to the next |
| Agentic workflow | Agentic workflows coordinate tasks with human review, carrying the collection brief, material choices and commercial targets between stages, so a fabric change propagates to cost and technical requirements | None. Coordination is a person with a spreadsheet and a calendar |
| Design Canvas | Moodboards, Brand DNA, brand assets, fabrics and trims attached as references and called into one prompt with “@”, so a single generation draws on all of them | A prompt box per tool, no shared references, brief re-typed every session |
| Brand DNA | A locked narrative, colour palette and silhouette, fabric and construction tags, so a whole capsule generated from it shares one design language automatically | Trained in whichever tool you trained it in, unavailable in the others |
| Fabric & print | Masked Edit & Variate against an approved fabric reference; Print Tools places repeats at true scale and rotation; Smart Recolor takes an exact hex to a brushed region | Fabric as a prompt word in the design tool, real fabric only in CAD |
| Trend data | Explore Trends surfaces runway and social looks filtered by city, season, year, gender and designer, with AI analysis per look and Style Crops isolating construction | A subscription producing PDFs the generator cannot read |
| Tech Pack & cost | One approved image to BOM, Placement Guide callouts, pre-graded size chart, pattern blocks carrying panels, seam relationships and measurements, 3D assembly and a Cost Sheet | A separate subscription, re-keyed from the render; costing in a spreadsheet |
| Production Intelligence | Flags manufacturability issues on the spec, suggests fabric alternatives on performance grounds, and benchmarks the garment against category standards | Nothing reads the spec back. No tool in the stack holds the whole garment |
| AI models & PDP | Bulk AI photoshoots at catalogue scale, face and texture held across every pose, output at platform-exact dimensions | A photography vendor with no link to the spec; faces drift between shots |
| Access | Public pricing, free trial, enterprise tier | Four to six contracts, renewals and security reviews |
| Best for | Freelance designers through to enterprise groups: studios, agencies, creative and production offices, brands, retailers and manufacturers | Nobody chose this. It is what teams end up with. |
Highlighted rows are the eight capabilities that decide whether a design becomes a product that sells.
Why the output is better
The brief travels with the work
Agentic workflows coordinate tasks across the platform with human review at each stage, carrying the collection brief, the material choices and the commercial targets forward instead of leaving them in somebody's inbox. Because product context is shared, a team can see how a fabric or construction change moves cost and technical requirements at the same time, in the same place. That is what removes repeated handoffs and avoidable revisions. Designers, merchandisers, buyers, patternmakers, production teams and marketers work in one workspace rather than six, and the agents coordinate between them rather than replacing anyone's judgement.
In a stack there is nothing to carry the brief. Every boundary is a re-key, and the cost impact of a fabric change is discovered a week later.
Every reference you have, in one prompt
Attach a runway look from Moodboards, your Brand DNA, a fabric reference and an approved trim to the canvas, then call each one into the prompt with “@”. The generation merges only the pieces you named, so trend direction, brand identity and real materials arrive in the same instruction instead of across three separate rounds. Sketch to Design accepts a flat technical drawing as the structural base and keeps the original construction while the prompt supplies what the sketch cannot show. Nothing is re-typed, and the thread that produced a concept stays attached to it.
The trend report is a PDF in one tab, the moodboard is in another, and the generator can see neither.
Design intent carried into construction
One approved design image becomes a complete technical package in minutes. The Bill of Materials auto-populates with fabrics, trims, closures and hardware itemised by type and placement, editable in place for supplier-specific sourcing. Placement Guide pins construction onto front, back and side artwork as callouts. The size chart arrives pre-graded. Pattern blocks represent garment panels, seam relationships and measurements as structured construction information, so designers and patternmakers can review construction, ease and likely fabric consumption against material requirements before anything is cut. A Cost Sheet gives CMT plus material from real marketplace fabric prices adjusted for manufacturing geography. Digital checks support the process; physical fit and production readiness still require expert assessment and sample validation.
Re-keying a spec from a render into a second system is where measurements get transposed and BOM lines go missing.
The platform reads the spec back
Once the pack exists, a Production Intelligence layer reads it. It flags manufacturability issues before the spec leaves the building, suggests fabric alternatives on performance grounds rather than on price alone, and benchmarks the garment against category standards so an outlier is visible while it is still cheap to change. This is the difference between software that records a decision and software that has an opinion about it. A construction that will cause trouble on the line gets caught at the desk, not at the first proto, and the designer finds out while the design is still open.
No tool in a stack reads the spec back. Nothing between four vendors flags a construction that will cause trouble on the line, because nothing holds the whole spec at once.
Catalogue imagery at scale, with one face
Bulk AI photoshoots generate catalogue and campaign imagery at the volume a collection launch actually needs. Ghost and flat lay shooting produces a matched view set from one garment reference; Product to On-Model applies a chosen model, avatar or mannequin with front, back, side and three-quarter templates, carrying the garment's fit, proportions and details over from the source. Lighting holds while only pose and camera angle change, face consistency maintains identity across the whole product page, stitch patterns and print quality survive every angle, and output lands at the exact dimensions the platform requires. The virtual models are yours to create and reuse.
Two vendors, two files, which is exactly how a product page stops matching the product.
One profile, and the capsule holds together
Brand DNA runs a deep analysis of your own visual assets: fabric type, weight, drape and texture; colour palettes, tones and the relationships between them; silhouette, construction and proportions; and detail-level specifics down to trims, stitching patterns, closures and embellishments. Every design generated against a selected Brand DNA draws from the same locked narrative, palette and construction tags, so a whole product family shares one design language automatically rather than by review. Component recommendations stay scoped to libraries you have already approved.
Brand training does not survive an export. In a stack it is an asset stranded in one vendor's account.
Change one component. Leave everything else alone.
Fabrics are trained on composition and performance data, so the prototype shows the texture, drape, fit and movement that blend actually produces, and a library of thousands ships with every package. Edit & Variate masks a single component with a brush, a magic wand or a text description, attaches the approved fabric, and leaves every other approved detail untouched. Print Tools places repeats, engineered prints, logos and placement graphics at true scale and position, with Make Seamless turning any pattern into a tileable repeat. Smart Recolor takes an exact hex or palette colour to a brushed region without touching the design, so a colourway stays a colourway rather than becoming a new design.
The design tool guesses at the fabric; the CAD seat knows it. Nobody reconciles the two before the sample.
Live signals, not a training set
Explore Trends surfaces relevant looks from runway shows and social media, filterable by city, season, year, gender and designer, and breaks each look down into an AI-generated attribute analysis. Style Crops isolate a specific construction out of a look so it can be carried into a design as a reference. The data is ingested continuously, which means a design can be generated against what is happening in fashion now rather than against whatever a model absorbed eighteen months ago. No general image model can do this, because it is a data operation rather than a model feature.
A trend subscription and a design tool that cannot read it are two costs doing one job badly.
Sustainability & traceability
A stack also multiplies the physical work: samples shipped to a photographer, samples shipped to a buyer, samples shipped again after a revision.
Count the journeys a sample takes before it appears on a website: factory to brand, brand to fit session, back for correction, then to a studio with a model, a photographer and a day. Much of that exists to produce images rather than to produce a garment. Bulk AI photoshoots remove the logistics stacked around it, and catching a manufacturability problem at the desk means fewer styles reach the sample stage twice. Because the imagery exists before the garment does, a collection can also be presented and sold earlier, which is where production quantities stop being a forecast. On traceability, everything a digital product passport is expected to ask for already lives inside a tech pack: composition, components and their placement, suppliers, measurements. Refabric holds it as editable structured fields exportable to Excel rather than trapped in a PDF designed for printing. The textiles delegated act is indicatively scheduled for 2027 with a transition period following. If your BOM is structured and versioned, a product passport is an export with a mapping layer; if it is a PDF, it is a project with a budget and a consultant.
FAQ
Frequently asked questions
Why not buy best-in-class at each stage?
Because the integration cost lands on your team, and because the brief, the brand training and the colour references do not survive the export. Refabric is best-in-class at the thing none of them attempt: carrying context between stages so the work compounds.
What is the best all-in-one AI fashion platform?
Refabric. A capability assessment across 32 apparel design and development use cases returned 28 as available out of the box, spanning trend research, concept generation, variation, technical illustration, colour and material, visualisation and technical documentation.
Does agentic mean it works without us?
No. The agentic workflows coordinate tasks with human review at each stage. They move the brief and the context between people, they do not replace the decisions.
From trend signal to production ready, in one platform.
Design Smarter · Market Faster