Who owns and runs Build-a-Dress?
Fig AI Systems does. Build-a-Dress is a live business the company built and operates at build-a-dress.com, with over 2,000 monthly active users.
Build-a-Dress: a live AI business Fig AI Systems runs
Build-a-Dress is a made-to-order fashion business Fig AI Systems built, owns and runs at build-a-dress.com, with over 2,000 monthly active users. Shoppers design a dress in minutes by talking to an agentic chat assistant. An automated workflow prices it and the order routes to a verified manufacturer.
LiveMarketplace
- Scale
- 2,000+ monthly active users
- Status
- Live business, running today
- Ownership
- Built, owned and operated by us
A product we own and run
Over 2,000 monthly active users design and order made-to-order clothing through this custom AI web application.
Build-a-Dress is a system we still have to keep running. It takes real orders, verifies real manufacturers and settles real money. When the agentic parts misbehave, we find out first - before any customer files a ticket.
A garment must be specified before pricing
Two things have to exist before an order does: a design precise enough to sew, and a price for a garment nobody has made.
Both requirements normally consume human time. Someone has to draw the specification out of the shopper. Someone who knows garment construction has to price it. Neither step scales: each new shopper adds another conversation and another manual estimate.
Build-a-Dress removes the wait from both steps. AI agents handle the design conversation and the price estimate. A person contributes the taste and the sewing.
How Build-a-Dress works: three stages
Each stage hands the design to the next in a form the next one can act on.
An agentic chat assistant talks to the shopper and produces a design. An agentic workflow classifies that design and returns a price. The marketplace routes the order to a verified manufacturer and settles the payout.
Splitting the work into three stages buys accountability. The design is settled before it is priced, so a quote traces back to what the system decided. That separation is what we apply in multi-agent orchestration and workflow automation generally. Each stage gets one job, and its handover is inspectable.
What is inside Build-a-Dress
Four systems make up the product: the design assistant, the quoting workflow, manufacturer verification, and payments.
Agentic chat assistant
Carries the design across the whole conversation, so a shopper can change one detail without losing the rest, and generates images as the dress takes shape.
Automated quoting
Reads the finished specification and classifies dress complexity, weight and the other signals that drive cost, so it can price designs it has never seen.
Manufacturer verification
The vetting that lets the platform call its manufacturers verified, and the payout setup that follows it.
Global payments
Stripe and Wise integrated to cover both sides: shoppers paying in, manufacturers paid out in another country and currency.
We offer the first as agentic chat assistant development and the second as AI workflow automation.
What running it in production demands
Build-a-Dress is live, so its agentic parts have to hold up in front of shoppers.
A design conversation has to stay coherent for someone who wanders off and comes back. A quote has to be defensible, because the business has to honour it. None of that work can wait until after launch.
What Build-a-Dress proves
It exercises three of our seven services against a system real shoppers use, and against orders the business has to honour.
The design conversation is agentic chat assistant development. The quoting engine is multi-agent orchestration and agentic workflow automation. Holding those together with verification, payouts and payments is custom AI agent development. See Report Grader for a second product in a different domain, or go back to all products.
Frequently asked questions
What does the Build-a-Dress chat assistant actually do?
It turns a conversation into a dress specification a manufacturer can work from. The assistant holds the design in state, so each answer refines the same garment. It generates images of the design, so the shopper can react to a picture.
How does Build-a-Dress price a dress that does not exist yet?
An agentic workflow classifies the design before it quotes it. It reads the specification from the chat and classifies dress complexity, weight and the other signals that drive price. The quote comes from those classifications, so no shopper waits on a human review.
Can Fig AI Systems build something like this for my business?
Yes. Build-a-Dress is the shape of system Fig AI Systems builds for other companies. A conversation becomes a specification, the specification becomes a price, and the price becomes a fulfilled order.