Industries · Retail
Vision and catalog data for retail
Dense, safety-first labels on unstable drone-delivery video, and hundreds of thousands of products sorted into one taxonomy with AI speed and human checks.
The problem
What makes retail data hard
Safety-critical vision
Delivery drones must spot people, pets, and fragile objects in backyards they've never seen.
Slow frames
Wind-blown drone footage took about ten minutes per frame to label properly.
Messy catalogs
Products from many sources use different names and categories, and LLMs alone hallucinate.
How MLtwist helps
One pipeline, built for this data
Our platform prepares and routes the data; our team, yours, or both label it. Every version ships with a Data ID Card.
- Tool selection
- We pick the labeling tool that handles high-motion video best, and tune pre-labeling to the footage.
- Safety-first taxonomy
- Classes for humans, pets, and fragile objects come first, with high recall checked in QA.
- AI plus human validation
- Models propose categories; trained reviewers verify each item against manufacturer and retailer sources.
- A taxonomy that scales
- One consistent framework for new products as they arrive.
Case studies
Retail programs we've delivered
Retail analytics platform · Retail
How MLtwist Supported a Retail Analytics Platform in Structuring Product Data at Scale
Retail company · Retail
Retail Company Uses MLtwist for Safe and Accurate Drone Delivery Vision
Related work
Bring us your retail data
Tell us the data type, volume, and timeline. We'll scope it with our team, yours, or both — and deliver it versioned, in your format.
Also available through Carahsoft and Google Cloud Marketplace.