17 Fashion Forge service lines delivered through a single WhatsApp number. Designers talk in plain language. Patterns and tech packs come back.
FashionBot is a WhatsApp business number that gives any fashion designer access to Fashion Forge's full AI + expert network — tech packs, patterns, sketches, sourcing, fitting coordination — all via text and voice notes, no app, no login, no minimum.
| Trigger / Intent | What the Bot Does | Wave |
|---|---|---|
| "tech pack for [garment]" | Runs Forge API → generates measurements, BOM, stitching, QC, care, labels → sends PDF link + assigns pattern maker for validation | Wave 1 |
| "sketch / flat for [garment]" | Generates technical flat (front + back) via Fal flux → sends images in WhatsApp + download link | Wave 1 |
| "first pattern for [garment]" | Generates pattern pieces, grading table, ease allowances, cutting instructions → assigns master for tacit-knowledge validation | Wave 1 |
| "find me a pattern maker for [spec]" | Matches from human network directory → returns 3 options ranked by specialization + lead time + price → books on confirm | Wave 2 |
| "production pattern" | Converts approved first pattern to full grade range, marker optimization, factory output formats (Gerber/Lectra/DXF) | Wave 2 |
| "source [fabric spec]" | Searches supplier database → returns 3 verified options with price/MOQ/lead time → coordinates swatch request | Wave 2 |
| "draping for [garment]" | Routes to human draper directory — cannot be significantly AI-automated. Returns human availability + pricing + booking. | Wave 2 |
| "design dev / development" | Trade-off analysis: cost-to-make vs. design intent, simplification options, BOM cost breakdown, pricing architecture | Wave 2 |
| "book a fitting" | Coordinates fit model from roster → schedules → sends address + deposit + day-of brief | Wave 3 |
| "estimate cost" / "what would this cost" | Returns materials + labor + trim + permit cost estimate for LA manufacturing based on garment type + fabric + size run | Wave 1 |
| "remember:" / brand notes | Stores brand fit DNA, preferred pattern makers, colorway preferences, factory contacts in PostgreSQL user record | Wave 1 |
| Voice note | Deepgram STT → intent detection → same flow as text commands. "Voice note me the details — I'll handle the rest." | Wave 2 |