AI Tech Packs for Fashion Brands: Draft Specs a Factory Can Use

A small brand can use AI to draft the wording, structure and tables of a tech pack, but not the numbers that make it work. Give a chat assistant your sketch, fabric names and a reference garment's measurements, let it assemble the sections, then check every measurement, trim and tolerance against a physical sample before a factory sees it.

The split matters because factories read a tech pack as an instruction, not as a pitch. A confident paragraph that says "chest 54 cm" when your pattern says 56 costs you a sample round, and a sample round costs weeks. AI is quick at the tedious parts: consistent section headings, a tidy construction list, a bill of materials with no missing rows. It is unreliable at anything that depends on a body, a fabric or a machine it cannot see.

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What a factory actually looks for in a tech pack

Pattern makers and sampling teams open a tech pack looking for answers to five questions. Which garment is this and which version? What does it look like from every side? How big is each part, and how much variation is acceptable? What is it made of, down to the thread? And in what order is it put together? Anything that leaves one of these open turns into an email, and emails turn into a sample that comes back wrong.

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A practical tech pack for a new style therefore has these sections, in roughly this order:

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1. Cover sheet. Style name and number, season, version and date, sizes in the range, base size, your contact, and a one-line description.
2. Flat sketches. Front, back and any side or detail views, drawn flat with every seam, pocket and stitch line visible.
3. Callouts. Numbered notes pointing at features: "1. Kangaroo pocket, topstitched 6 mm from edge".
4. Point-of-measure (POM) table. Each measurement named, how it is taken, the base-size value, the grade between sizes and the tolerance.
5. Bill of materials (BOM). Fabric, lining, thread, zips, buttons, labels, drawcords, packaging, each with supplier reference, colour, size and placement.
6. Construction notes. Seam types, stitch counts per inch or per 3 cm, finishing, pressing and any hidden detail.
7. Colourways and artwork. Colour references, print placements and sizes.
8. Labels and packing. Care and size label positions, folding, polybag and carton instructions.
9. Revision log. What changed between versions and who requested it.

The sketches are the part AI image tools handle worst, so I would keep those in your own hands or with a freelancer. Everything else in the list is text and tables, which is where a chat assistant earns its keep. If you want the wider picture of using AI at the design stage, the tutorial on AI tools for clothing designers covers mock-ups, and this one stays on the specification itself.

Gather the raw inputs before you open any AI tool

The quality of the draft is set by what you paste in. Spend ten minutes collecting these, because a tool fed only a photograph will invent the rest:

• One photo or sketch per view of the garment, with your own notes on a printout if it helps.
• A reference garment you already own that fits the way you want, and its measurements taken flat with a tape.
• Your fabric choices with weight (grams per square metre) and composition from the supplier's swatch card.
• Any trims you have already sourced: fastener type and length, button diameter, label size.
• The size range and grade rules you intend, even if rough ("each size up adds 4 cm to chest").
• Your factory's template if they have one. Many do, and a draft in their format is read faster than one in yours.

Put it all into one document or one chat message. Do not let the tool guess. If you do not have a value yet, write "unknown" beside it so the draft carries the gap instead of filling it with something plausible.

A main worked example: a heavyweight hoodie

Illustration only. Say a four-person streetwear label is developing a heavyweight pullover hoodie for its second drop. The founder has a sketch front and back, a hoodie she likes from another label, 380 gsm brushed-back cotton fleece, and a plain pull-on design with no fastenings and a kangaroo pocket.

She measures the reference hoodie lying flat on a table, then pastes the numbers into the assistant with the instruction below.

You are helping me draft a garment tech pack for a factory.
Style: HD-02 Heavyweight pullover hoodie, size range S to XL, base size M.
Fabric: 380 gsm brushed-back cotton fleece, 100% cotton. Rib: 2x2, same colour.
Reference garment measurements (flat, in cm, size M):
Chest width (armpit to armpit) 62; Body length (HPS to hem) 70; Shoulder drop 8;
Sleeve length (shoulder seam to cuff) 62; Hem width relaxed 52; Cuff opening relaxed 9;
Hood height 36; Kangaroo pocket opening 22 each side.
Grade: S to M +4 cm chest, +2 cm length, +1 cm sleeve; same steps M to L, L to XL.
Tasks:
1. Build a point-of-measure table with columns: POM code, description, how to measure, M value, grade, tolerance (+/-).
2. List the construction notes you would expect for this style, marked as SUGGESTION.
3. Draft the BOM with columns: item, description, supplier ref (UNKNOWN if not given), colour, size/spec, placement.
4. List every value you assumed rather than took from my notes, under the heading ASSUMED.
Do not invent supplier references, stitch counts or tolerances. Write UNKNOWN instead.

The last two lines are the important ones. The assistant returns a table in two minutes that looks finished. The ASSUMED list shows where it filled a gap anyway, and the UNKNOWN rows show what she has to chase. That is a better outcome than a polished page that hides its guesses.

Say the draft comes back with a tolerance column reading "+/- 1 cm" for every row. She knows from her factory's last order that tolerance is tighter on length than width, and different for sleeves, so she overwrites it. She also notices the draft lists "chest 62 cm" as the half-width but labelled it "chest circumference", which would have been read as a 62 cm garment, about half the intended size. That single wording error is exactly what the check in the next section is for.

The measurement table, line by line

Most tech pack errors live here, so it deserves its own pass. A good POM table tells the factory what is measured, where, and how much leeway they have. The same hoodie in a filled-in form looks like this (illustrative values, with the tolerance column for her to confirm with her factory):

Three checks make the table safe to send:

1. Half versus full. Decide once whether every chest and hem value is a flat half-width or a full circumference, and say so in the header. AI mixes the two readily.
2. Grade arithmetic. Multiply out the grade yourself. From M at 62 cm chest, L should be 66 and XL 70. Ask the tool to print the whole size run, then check three cells by hand.
3. Measure the sample, not the pattern. When the first sample arrives, measure it against the table and write the real values beside the intended ones. Those become the next version's table.

A short prompt that does the third check for you: paste the intended table and your measured sample values, and ask for a comparison listing only the rows where the difference is bigger than the tolerance. The tool is good at this kind of side-by-side subtraction, and you can verify each row against the tape in seconds.

The BOM: where AI saves time and where it pads

A bill of materials is a list of every physical thing that ends up in or on the garment. Missing a row is the common failure: nobody specified the care label, so the factory sourced a generic one in the wrong place, or the drawcord was left as "to match". A prompt that asks for a "complete BOM for a pullover hoodie" will list items you did not choose, such as eyelets or reflective tape. Use that as a prompt for thought, never as a to-do list to send onward.

For the hoodie, the filled-in BOM looks roughly like this (illustrative):

Every UNKNOWN is a decision for you or a question for the factory. Ask the tool to turn them into a list of questions, grouped by who can answer: your fabric supplier, your label printer, or the factory. That list is the useful by-product of the whole exercise. If you want to carry the finished BOM into pricing, the tutorial on costing a style from its tech pack picks up from there.

Construction notes without invented stitch counts

This is the section where a language model sounds most authoritative and is least reliable. Ask it for "construction details for a hoodie" and you will get confident-looking lines like "flatlock seams at 12 stitches per inch". That might be right for one factory and wrong for another, and the assistant has no way to know which. It is writing what hoodie tech packs usually say.

A safer pattern is to give it a rule and make it quote its source:

Write construction notes for HD-02 using only the facts I give you below. For anything else, write
"FACTORY TO ADVISE: [topic]" so I can ask. Facts: topstitch 6 mm from edge on pocket opening;
shoulder seams taped; hood is two-piece with a centre-seam; rib cuffs and hem attached with overlock,
then turned in; no bartacks except pocket corners.

The result is a short list, mostly "FACTORY TO ADVISE" lines for stitch type and density, and your own facts rewritten tidily. That is the point. The factory fills in the technical blanks from its own machine capability, which is more reliable than a model's recollection.

Send it, then run the feedback loop

A tech pack is a conversation document. The brands that get clean samples quickly are the ones that treat the factory's first questions as input to a better version, not as an interruption. Here is a loop that keeps the AI part cheap:

1. Version 1 goes out with its UNKNOWN rows visible, and a note saying which rows you want help with.
2. Collect the factory's questions in one place. Paste the emails or messages into your assistant and ask it to turn them into a table: question, section affected, proposed answer, who decides.
3. Answer in batches, then ask the assistant to produce a revision log line for each change ("V2: hem rib width 8 cm finished, was 7 cm, per factory advice").
4. Update the file and the name. HD-02_v2_2026-11-05 beats "final_final".
5. When the sample arrives, measure it, photograph any faults against the callout numbers, and feed both into the same chat to draft the corrections list.

An illustration of step 5: the sample hoodie arrives and the hood sits 2 cm lower than the reference. She photographs it and writes "hood height 34 vs spec 36" in her notes. The assistant turns that into a one-line correction ("POM G hood height: sample 34, spec 36, tolerance CONFIRM; request pattern adjust +2") and a note on the likely cause, flagged as a guess for the factory to confirm. She forwards the line, not the guess.

What AI gets wrong, with the signs to look for

These are the failures I would test for every time, because each one has a recognisable look:

• Plausible numbers with no source. The sign is a table with no UNKNOWN or CONFIRM cells at all. A real first draft always has gaps. If it has none, the tool filled them.
• Mixed units. Centimetres in one table and inches in another, or a gsm figure given as ounces. Set one unit at the top of your prompt and search the output for the other.
• Half versus full confusion. Covered above, and the most expensive mistake of the lot because everything else in the table looks right.
• Hallucinated trims. A zipped side pocket or a set of press studs appears in the BOM when your style has neither. Compare the BOM against your sketch line by line.
• Generic tolerances. A blanket "+/- 1 cm" is the tool's habit, not a standard. Tolerances depend on garment type and the factory's capability.
• Overconfident care and content wording. Fibre content and care symbols must match the real fabric and the rules where you sell. Use the supplier's own test report, and ask an adviser if you are unsure of the legal wording.
• Silent changes between versions. When you paste an old table and ask for edits, the assistant may alter cells you did not mention. Ask it to list exactly what changed, then compare against your original in a spreadsheet.

A quick way to catch most of this: ask the tool, in a fresh chat, to act as a sampling technician reading the pack, and list every question it would need answered before cutting fabric. The questions it asks are often the ones the factory would have asked, for free and before you pay for the sample.

Run on the HD-02 draft, the reply might read like this (illustrative):

Questions before cutting HD-02:
1. Chest 62 cm and hem 52 cm: half measurements or full circumference? The table header does not say.
2. Hood lining: same fleece, but brushed side facing in or out?
3. Drawcord: how does it exit the hood channel? Eyelets or buttonholes? Nothing in the BOM.
4. Cuff rib is 9 cm relaxed: what is the sleeve opening before the rib is attached?
5. Kangaroo pocket: single layer with turned edges, or bagged?
6. Care label: who supplies the wording and wash symbols?

Five of the six are genuine gaps she can close in ten minutes; the care-label question was already on her list for the label printer. The drawcord question is the useful catch. The BOM has a cord but nothing says how it leaves the hood, which is exactly the kind of omission that comes back as a sample with buttonholes where she wanted metal eyelets. She answers each question in the pack itself and ignores the answers the tool offers to its own questions, because those are guesses dressed as advice.

Where the time goes and what it saves

Illustrative sums only, so replace them with your own. A first tech pack from scratch in a spreadsheet takes a small brand perhaps three to four hours when the maker knows the style: sections, tables, BOM, notes. With a good set of inputs and a draft from an assistant, assembling and formatting falls to about an hour, and the checking you would have had to do anyway takes another hour. The saving is in the typing, not in the thinking, and it grows with the second and tenth style because the prompt and template are reusable.

What it does not save is sampling. A tech pack is there to make the first sample closer to what you want, not to skip it. If your plan counts on no fit sample at all, no amount of AI drafting rescues it.

Make the prompt reusable

Once HD-02 is through sampling, strip out the specifics and keep a template. Save it in a Claude Project or a ChatGPT Project with your base size, unit rules, grade rules and the standing instructions "never invent, mark UNKNOWN". A new style then starts from a prompt with the same guardrails and a fresh set of inputs. Two additions earn their place: a standard ASSUMED list at the end of every draft, and a standing line that every table must say whether it is half or full circumference.

If you design several styles a season, this also gives you consistent shape across packs, which factories notice. And if you are weighing what else AI could do across a clothing brand, the pieces on line sheets for buyers and production timelines reuse the same product data you have just cleaned up.

A checklist before you press send

1. Every table states its units and whether widths are half or full.
2. Three random grade cells re-added by hand.
3. BOM compared line by line with the sketch; nothing in it you did not choose.
4. No UNKNOWN, CONFIRM or FACTORY TO ADVISE left unless you meant the factory to answer it, and the cover note says so.
5. Fibre content and care wording from the supplier's own report.
6. Version number and date in the file name and cover sheet.
7. Revision log current.
8. A second person has read it once, preferably someone who has handled the reference garment.

Done this way, AI is a fast and fairly tireless assistant for the writing and tabulating parts of a tech pack, and a poor guarantor of facts. The brand stays responsible for every number the factory will build from.

Questions brands ask about AI-drafted tech packs

Can AI generate a tech pack from a photo alone?

It can describe the garment and suggest a first layout, but it cannot know your measurements, fabric weight, stitch density or trim sizes. A photo gives a plausible-looking guess. Treat the output as a draft of the wording and structure, then fill every number from your own pattern, a reference garment or the factory's own specifications.

Should I send the factory a PDF or a spreadsheet?

Send both if you can. A PDF keeps the sketches and callouts fixed, while a spreadsheet lets the factory paste your measurement and BOM tables into their own sheets. Whatever you send, version-number it in the file name so nobody works from an old copy.

How many fit samples should I expect to need?

It varies by factory and by how complex the style is. Plan on at least a first sample and one corrected sample for a new style, and treat any style that passes at first sample as a bonus. A clearer tech pack reduces avoidable rounds but never removes the need to try the garment on a body.

Do I need to disclose AI use to the factory?

Any such obligation would sit in your supply agreement, so check that first. Either way, it helps to be plain: tell them which parts you drafted with a tool and which you measured yourself. The factory then knows where to ask questions rather than assuming every figure was checked on a physical garment.

Further reads

• AI Tools for Clothing Brands: From Sketch to Tech Pack to Listing — Sketch to tech pack to online listing in one flow.
• AI Textile Design Generator: Make Print Repeats for a Small Brand — Prepare print artwork the tech pack can reference.
• Automation in Clothing Manufacturing: What a Small Workshop Can Automate — Order intake, tech pack checks, fabric and cutting-plan sums, production tracking and customer updates for a cut-and-sew workshop, with tool costs and limits.
• AI Tools and AI Development: The Complete 2026 Guide — the AI hub, including every tutorial in the AI-for-business series.

Sources: Claude help centre page on Projects (files and project instructions); OpenAI help centre page on ChatGPT Projects; general garment-industry specification practice. No vendor pricing is quoted.