Textile & apparel software, built around your business
Yukti AI builds a custom system for your textile or garment business — a design catalogue with visual search, size and colour-wise stock, job-work and process tracking for dyeing, printing, embroidery and stitching, a party-wise ledger, GST billing and a WhatsApp order bot. Ready-made textile packages give you fixed modules. We build around how you actually work — with AI watching your stock, your ageing designs and your orders.
Textile and apparel software is one system that runs a textile or garment business — a design catalogue with visual search, size and colour-wise stock across greige and finished goods, job-work and process tracking for dyeing, printing, embroidery and stitching, a party-wise ledger, GST billing and a WhatsApp order bot. Yukti AI builds it custom around your position in the chain — weaver, processor, wholesaler, agent or garment brand — with an AI layer that watches stock, ageing designs and parties who are slipping. Live in weeks, one-time build with 12 months of support.
The trade runs on thousands of designs and a lot of WhatsApp.
Thousands of designs across folders and chats, the same set sent to every party, prices retyped each time. Finding "something like this one" means scrolling for an hour.
Greige in one register, finished in another, stock by design, size and colour that no one can see in real time. Job work out for dyeing or printing and half-tracked.
Party-wise outstanding, agent commission and lot/thaan tracking spread across books and Excel, with orders taken over WhatsApp and re-entered by hand.
How a textile & apparel business actually runs
Surat is the centre of India's man-made fabric industry, and the trade here is not one business — it is a chain of them, each with its own way of working:
- Weavers and knitters produce greige (unfinished) fabric by quality and construction, tracked in metres and thaans.
- Processors take greige in for dyeing, printing, embroidery and finishing — job work, where fabric physically leaves the building and has to come back, matched lot for lot.
- Traders and wholesalers hold finished stock by design, colour and size, sell to retailers through agents, and run on party-wise credit.
- Agents carry catalogues, book orders and earn commission per party and per design.
- Apparel brands and garment units manage a style master, size ratios, cutting and stitching job work, and sell across their own store and marketplaces.
What ties all of them together is that the business is design-driven — a trader might hold thousands of designs, each in several colourways — and order-taking happens on WhatsApp. A buyer sends a photo: "do you have this, or something like it, in these colours". The person who can answer that fastest wins the order.
A textile system has two jobs a generic ERP never does well: find a design by its picture across a huge library, and track fabric that is out for job work without losing a metre. Everything else — stock, ledger, billing — is table stakes.
Why ready-made textile ERP falls short
Packages like Marg, BUSY or a generic garment ERP will give you a stock module, a billing module and a ledger. They are built for a standard trading flow and they charge per user, per year. Where they struggle:
- Designs are just codes. There is no way to search "find me designs like this one" — and in a design-led trade, that is the single most common question.
- Job work is bolted on. Issuing a lot for dyeing, tracking what is with which processor, and reconciling shrinkage on return is either missing or generic.
- The catalogue lives outside. The WhatsApp catalogue every trader actually sells from is maintained by hand, in a separate app, and goes stale.
- No AI. Ageing designs, slow-moving colours, parties who have stopped ordering — the package holds the data but never tells you.
- You adapt to it. A processor, a trader and a brand have very different processes; a fixed package makes all three work its way.
What a custom textile system needs to do
Built around your position in the chain, a custom system covers:
- A design master with visual similarity search over the whole library, colourway sheets and design-code reading
- Stock by design, colour and size — greige, finished and lot-wise — moving on every purchase, production, job-work issue/return, sale and return
- Job-work and process tracking matched to your actual processes (dyeing, printing, embroidery, stitching), with lot reconciliation
- A party-wise ledger, agent-wise commission, and GST billing generated from orders
- A WhatsApp catalogue and an AI order bot working off the same design master
- An AI layer that watches ageing designs, slow lots, stock and outstanding, and prompts follow-ups
For mills, processors and garment units the production side is the same discipline as any plant — see manufacturing ERP software — and the full textile module list is on textile ERP software. Our yarn manufacturing ERP shows the inquiry-to-dyeing-to-e-invoice flow end to end.
Everything a textile or apparel business needs.
We build only the parts you need — but designs, stock, job work, orders, ledger and billing all live in one system.
Catalogue + visual search
One design master; find similar designs by image; handle colourway sheets and design codes; generate a client catalogue and send it on WhatsApp.
Size & colour-wise inventory
Greige and finished-goods stock by design, size and colour, moving itself on every purchase, production, sale and return — with reorder alerts.
Job work & process tracking
Issue lots for dyeing, printing, embroidery or stitching, track what's out and back with each job worker, and see every lot's stage.
Order & dispatch
Take orders on WhatsApp or web, convert to a challan and invoice, and track to dispatch — with lot / thaan / piece detail.
Party ledger & agent commission
Party-wise outstanding in one screen, agent-wise commission calculated automatically, GST invoices generated from orders.
AI layer
A daily briefing on sales, stock and outstanding; alerts on ageing designs and slow lots; and automatic follow-ups to parties.
Want help applying this to your business?Send us your current setup on WhatsApp. Free workflow audit, reply the same day — in Hindi, Gujarati or English.
Get a free workflow auditEverything the textile packages do — and visual search on top.
Textile and garment ERP packages give you fixed modules and charge per user. Here's what they offer — and what we add.
How AI helps a textile business specifically
"AI" in a textile system is not a chatbot — it is analysis of the two things a textile trader worries about most: which designs are making money, and which parties are slipping.
- Visual search & matching — a buyer sends a photo; the system returns the closest designs you actually hold, in stock, with prices. This is AI doing the salesperson's fastest trick, instantly.
- Ageing-design alerts — designs and colourways that have not moved in N days, with the capital tied up in them, so you discount or clear before it becomes dead stock.
- Party drift detection — a regular buyer whose order frequency or value has dropped, flagged for a call before they are gone.
- Slow-lot & job-work alerts — a lot out with a processor longer than usual, or a shrinkage pattern worth questioning.
- Daily briefing — sales, top and bottom designs, outstanding by party, and lots due back — the state of the business each morning.
- Plain-language questions — "which designs sold best in Rajasthan last month", "how much fabric is out for printing", "which parties are over their credit limit".
Has Yukti AI built visual search for a textile design library?
Yes. Yukti AI built AI image similarity search for a Surat textile design house (name withheld) in about 7 days. Staff pick a category such as Saree, Kurti & dup or Dupatta, then upload a fabric photo or type a description like “pink floral border design”. The system returns the eight closest designs in that category, each with its design code and a similarity score.
The design house makes digital print and embroidery-look designs for ladies’ ethnic wear — suit and kurti & dupatta sets, sarees, dupattas, lehenga, daman and all-over prints. Its library of roughly 80,000 design images in about 1,000 sets could only be searched by folder and filename, and most files are colourway sheets: one large main panel plus narrow strips of the same design in other colours. The client’s rule was motif first, colour second.
| Client | A Surat textile design house (name withheld) |
|---|---|
| Library | Roughly 80,000 design images in about 1,000 sets, each design with a numeric code; the system is designed to index all of it |
| Before | Designs findable only by folder name and filename; no way to search by what a design looks like |
| Search by | A fabric photo or a typed description, inside one of six categories: All Over, Saree, Kurti & dup (suit sets), Dupatta, daman and Lehengha |
| Results | The top 8 designs in the chosen category, each with its design code and similarity score |
| Colourway sheets | A main-panel detector crops each sheet at the divider line; it found the divider in 67 of 67 suit colourway files, and the worst measured case moved from rank 70 of 97 to rank 1 |
| AI model chosen | Google Vertex AI multimodal embeddings, chosen over an OpenAI caption pipeline after a head-to-head test on a 401-design test catalogue |
| Privacy | No catalogue image was made public; query photos travel as file uploads, not hosted links |
| Build time & status | About 7 days; live, with two search apps over the 401-design test catalogue and an n8n search workflow over a 97-design index, tested end to end. Indexing the rest of the library is the next step. |
| Stack | Python, Flask, Pillow, NumPy, Google Vertex AI, OpenAI, Pinecone, n8n |
How staff find a design from a customer’s fabric photo
A customer sends a photo of the fabric they want. Staff choose the category, upload the photo, and the system compares it with every design in that category and lists the closest matches. The highlighted steps are the AI.
Google Lens searches the public web and has no API for searching a private catalogue, so it cannot tell a design house which of its own unpublished design codes a photo matches. The Google tool that can is Vertex AI multimodal embeddings, used for private vector search over your own files — and that is what this build uses.
Can visual search work for your saree, suit or dupatta catalogue?
Very likely, if your catalogue is large, visual and filed by code — and it can be measured on sample files from your own library before you commit. The same approach fits print and embroidery design houses, saree, suit and dress-material traders who receive fabric photos from buyers, and dupatta, kurti and lehenga suppliers whose designs come in several colourways.
The build returns design codes and scores. Connecting the search to a WhatsApp bot or website, adding filters such as fabric or stock status, or linking results to an ERP are possible next steps — options, not features of this build. Read the full textile design visual search case study for the recon of real files, the rank measurements and the OpenAI vs Google Vertex AI comparison.
The two search apps are custom web apps that also work on a phone — the kind of internal tool covered on app and web app development in Surat. On the ordering side of the trade, Yukti AI built a self-serve B2B ordering system for a digital fabric-printing firm: a catalogue web app and a WhatsApp ordering flow, with Razorpay payment and Shiprocket shipping wired in.
Want help applying this to your business?Send us your current setup on WhatsApp. Free workflow audit, reply the same day — in Hindi, Gujarati or English.
Get a free workflow auditWhat each person works with.
Owner
The daily briefing, design and party performance, outstanding, and overall stock and job-work position.
Sales / agent
The catalogue, visual search, order booking, their parties and commission — usable from a phone on the road.
Stock / godown
Stock in and out by design, colour and size; lot issue and return; reorder alerts.
Job-work coordinator
Lots issued to each processor, what is due back, and reconciliation on return.
Accounts
Party ledger, GST invoices from orders, agent commission, and payment tracking.
Design
The design master — codes, colourways, images — kept clean so search and the catalogue stay accurate.
Connected to what you already use
- WhatsApp Business API — catalogue sharing, an AI order bot, and order and payment updates
- Tally / accounting — push invoices and ledgers so your accountant keeps working the way they do
- Marketplaces — Amazon, Flipkart, Myntra and Meesho order ingestion and stock mapping, for apparel brands (the pattern from the Backdrop case study)
- Razorpay — payment links and reconciliation
- Shiprocket / courier — dispatch and tracking for brand and web orders
AI automation for textile and garment businesses: what sits on top of the ERP?
An ERP gives a textile or garment business one record of orders, lots, stock, parties and payments. AI and automation are what act on that record. For a Surat trader, a garment unit or a dyeing house, the realistic jobs are: WhatsApp order taking that turns a buyer's message into a draft order for staff to confirm; design and catalogue search from a fabric photo; dealer CRM follow-ups that tell each salesperson whom to call; payment reminders on WhatsApp and by Hindi voice call; stock and slow-design alerts; defect and QC logging by line, operation or lot; and a daily owner briefing in plain language.
Some of this is built and some is buildable on the same data, and we keep the two apart. Built: AI design search over roughly 80,000 designs (case study), a WhatsApp inbox that pre-fills yarn inquiries (Filyarn), piece-level garment tracing with karigar piece rates (Wewok) and a Hindi payment-reminder voice agent (voice AI payment reminders). Buildable: AI reading messy order messages and voice notes, flagging unusual dyeing loss, spotting defect patterns and briefing the owner each morning.
The full picture, with a stage-by-stage table, honest limits and an FAQ, is on our page for AI automation for textile and garment businesses in Surat. Related reading: AI ERP, AI CRM, ERP-connected AI agents, WhatsApp automation and workflow automation in Surat.
Textile systems we've built.
Textile design house — visual catalogue search
A catalogue and visual-similarity search over a design library in the tens of thousands — upload a design and find similar ones, with colourway-sheet and design-code handling.
Case study: garment manufacturing ERP
Wewok, a Surat sportswear brand: fabric and dyeing, programmes, cutting, bundles, karigar piece rates, QC and scan-and-trace of every garment.
Case study: yarn manufacturing ERP
A dyed-yarn manufacturing ERP and textile CRM for Filyarn Industries, Surat — WhatsApp inquiry to quotation, dyeing, QC, GST e-invoice and brokerage.
Backdrop — apparel inventory
Stock by product, size and piece; retail-sale decrement; Amazon listing mapping. Refined across versions for speed.
AI Business Management System
The full picture — CRM, ERP, billing and WhatsApp in one custom platform, with AI built in.
Common questions.
Run your textile business
on one system?
Tell us how your business works today — designs, stock, job work, parties. We'll show you what one system would replace, with visual search on top.