Project Scope

Project Scope

CLIENTMotives Vietnam
MARKETVietnam
INDUSTRYFashion / Apparel Manufacturing
CATEGORYAI Solutions – Intelligent Document Processing
TAGS#AI #DocumentProcessing #SupplyChain

The Context

In global apparel and home furnishing supply chains, converting brand Techpacks into accurate Bills of Materials (BOMs) is a high-stakes, labor-intensive process. Errors cascade directly into production mistakes, sourcing delays, and quality failures. Motives Vietnam is a global supply chain management company providing sourcing, product development, and quality assurance services for apparel and home furnishing brands across the US, Europe, and Japan. As order volumes grew, the limitations of a manual BOM creation process became a critical operational risk.

The Challenge

Three bottlenecks in the existing BOM creation workflow were limiting throughput and consistency:

Staff dependency
BOM creation relied entirely on experienced merchandisers and technical staff interpreting complex Techpack documents manually, making the process difficult to scale

Item code matching
matching Techpack specifications to existing master data, historical BOMs, and prior order records required significant manual effort and deep domain expertise

Scale limitations
maintaining speed and consistency at higher volumes was not feasible with the existing approach

The Solution

An AI-powered Intelligent Document Processing solution automated the full BOM creation workflow from Techpack upload to production-ready output:

01

File Reading and Data Extraction

AI reads and interprets uploaded Techpack files, automatically extracting structured specification data for processing
02

Item Matching and BOM Generation

AI matches extracted items against master data, historical BOMs, and prior orders to generate a draft BOM with accuracy scoring
03

Review and Validation Interface

merchandisers review AI-generated BOMs, flag exceptions, and confirm or correct outputs through a structured validation workflow
04

Continuous Learning

the system learns from staff corrections and feedback, continuously improving matching accuracy over time

The Result

50-7050-70%
reduction in BOM creation effort and processing time per Techpack
90-9590-95%
item mapping accuracy from improved structured data consistency
ScalableScalable
AI-assisted workflow enabling significantly higher order volumes with reduced manual dependency
Diliverry Model

Delivery Model and Execution

  • AI model training on Motives Vietnam’s master data, historical BOM library, and Techpack archive
  • Web-based upload, review, and export interface for merchandising teams
  • Feedback loop integration for continuous accuracy improvement post-deployment
Technology Stack

Technology Stack

  • AI: NLP and structured data extraction for Techpack interpretation
  • Matching engine: Semantic item matching against master data and historical records
  • Application type: Web-based document processing platform with human-in-the-loop review
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Stephanie Lee
MERCHANDISING LEAD | MOTIVES VIETNAM
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