← All workIntelligent warehouse label capture0→1 · Solo build

WMS Label Recognition

Turn label photos into warehouse-ready fields.

Extract manufacturer lot numbers, manufacture dates and expiry dates, with a standard API connecting recognition, human review and WMS entry.

MY CONTRIBUTION

Workflow design · Recognition service · API delivery

recognition accuracy
100%
logistics users
28
calls per day
~520

A better way to work

BEFORE

Warehouse staff manually locate and type label details while dealing with inconsistent layouts, date formats and similar-looking characters.

WITH THE PRODUCT

A photo produces structured fields for review. Staff confirm or correct the result, and the business application completes WMS entry.

Core capabilities

01

Capture the fields that matter

Extract the manufacturer lot number, manufacture date and expiry date directly into the fields warehouse teams need.

02

Keep review in the workflow

Structured results remain editable, with missing information left empty. Staff retain control of the final confirmation.

03

Fit existing warehouse operations

A PHP JSON API, timeout handling and feedback interface let the calling application connect capture, display, review and entry.

How it works

  1. 01

    Photograph the label

  2. 02

    Extract lot and dates

  3. 03

    Review or correct fields

  4. 04

    Confirm and enter into WMS

Key design decisions

01

Design the output around three fields

Warehouse entry needs a manufacturer lot number, manufacture date and expiry date. I shaped the service around those structured fields so the business application can display and enter them directly, keeping review focused on the information staff need.

02

Leave the final check with the user

Recognition is followed by review and correction, with absent label information left empty. Staff retain final confirmation, turning character-by-character typing into a focused review of the extracted fields.

03

Connect through the existing workflow

A PHP JSON API provides recognition while the existing business application handles capture, display, confirmation and WMS entry. Timeout handling and feedback interfaces let the caller manage exceptions and support manual intervention.

PRODUCT / ENGINEERING

What I delivered

PHPVision ModelJSON APIHuman-in-the-loop

I designed the workflow, compared vision models with OCR-based approaches, and built the demonstration and PHP recognition API. I defined request formats, structured outputs, timeouts and feedback interfaces for integration into the business application.

TRY THE WORKFLOW

Recognize. Review. Confirm.

INTERACTIVE WALKTHROUGH

This walkthrough uses sample data and preset results, without connecting to company systems or live AI.

Label recognition workspace
INPUT · SAMPLE LABEL
LAB / SAMPLE01
SAMPLE REAGENTREF. DEMO-A01 · 10 mL
LOTLT260901
MFG2026.09.01
EXP2027.09.01
FOR DEMONSTRATION ONLY

Make every field reviewable

Select a label, inspect its fields and explore the review, correction and confirmation flow.

Does your team face a similar challenge?

Start with one workflow. Let’s explore how AI could fit your operations.

Discuss your project
CONTACT / COLLABORATE

What would you like to solve?

Get in touch about enterprise AI, workflow automation, practical AI training and adoption, or career opportunities. I’m also happy to discuss independent product design and development. Start with your workflow and the outcome you have in mind.