Product Data Cleaning
Turn your product data
into a shoppable assortment
From messy
product
data to clean records
Product data quality for your PIM: every
attribute checked
against titles, descriptions
and images, with a source for every change.
Supplier data → Zenline
| Source | Attribute | Before |  After |
|---|---|---|---|
| Image | Color | blk | Black |
| Brand rules | Brand | AURORA audio inc. | Aurora |
| OEM data sheet | Connectivity | missing | Bluetooth |
| Description | Noise cancelling | nc | Active |
| Normalized | Pack size | 1 pcs | 1 piece |
- Source
- Image
- Attribute
- Color
- Before
- blk
- After
- Black
- Source
- Brand rules
- Attribute
- Brand
- Before
- AURORA audio inc.
- After
- Aurora
- Source
- OEM data sheet
- Attribute
- Connectivity
- Before
- missing
- After
- Bluetooth
- Source
- Description
- Attribute
- Noise cancelling
- Before
- nc
- After
- Active
- Source
- Normalized
- Attribute
- Pack size
- Before
- 1 pcs
- After
- 1 piece
Your whole
assortment,
in every
filter and every search
Correct colors and& variants
Vision-language models compare titles and attributes with product images and flag colors, sizes or variant names that don’t match before shoppers notice them.
Title vs. product image
Product image- Color in title
- Midnight blue
- Color in image
- Black
- Result
- Mismatch flagged
Complete attributes for filtering
Missing values are filled from technical data sheets and manufacturer websites, each with its source, so products stop dropping out of filters and search.
Filled attributes
With source- Battery life
- Up to 30 hours
- OEM website
- Noise cancelling
- Active
- Technical sheet
- Weight
- 250 g
- Technical sheet
- Compatibility
- iOS, Android
- OEM website
One clean record per product
Near-duplicates are merged, variants harmonized and brands spelled one way, so substitutes, bundles and promotions keep working, also on Black Friday.
Near-duplicates found
- Aurora OLED 55″ blackDuplicate
- AURORA OLED55 BlkDuplicate
- Aurora 55 inch OLED TV, blackDuplicate
Merge into one record with harmonized variants
“In a market flooded with overcomplicated tools, Zenline AI brings the clarity and centralization category teams need.
The value was
obvious for us from day one.”
Up and running
1 week
Zenline starts on
public data, so your
insights need no IT project.
Day 1
Start on public data
Agents read your assortment from your website and from marketplaces.
Week 1
Add internal data
Sales, margin, PIM, inventory, loyalty program, website traffic and promotion data arrive as weekly uploads, without deep ERP integration.
Every week
Decide with the agents
Every recommendation comes with its reasoning, its sources and the expected effect.
Throughout
Your Zenline engineer
A forward deployed engineer sets up your data, runs the first weeks with you and stays your contact. Nothing for your IT to do.
What comes
after
clean
product data?
Product Matching
Substitutes, variants and complements are matched on clean attributes. Shoppers see the right alternative, and you find private label gaps and decide what to launch or delist.
Company Brain
One digital model of your company with all its products. It holds your team’s assortment strategy and experience, grows and learns with your team, and shapes every agent recommendation.
FAQs
Zenline AI uses AI agents to harmonize and clean all assortment and price data. This is the foundation that lets the AI agents work cleanly across the assortment. To do this, the agents check your product data with text and image models and harmonize terms, attributes, units, and brand and variant names, so the same attribute is always described the same way. Zenline fills missing attributes from product sheets and manufacturer websites, and duplicates and conflicting entries are resolved. This data cleaning is a standard process for every customer.
Everything you can imagine: color, size, capacity, compatibility, pack size, brand and variant names, plus the category-specific attributes your filters rely on. The agent also checks titles and attributes against product images.
Zenline AI works with every PIM system. Agents and team adapt to your setup.
Yes. If your data must stay in-house, Zenline runs on-premise in your own data center or private cloud. Otherwise every customer gets a completely separate environment, hosted in Europe. Either way, your data is not used to train models.
