TREN

E-commerce · Scope to be defined during discovery

AI System for Adapting Product Listings to Marketplace Rules

We design an AI system that reviews the central product record and channel rules together with source and freshness information. The system prepares a channel-compliant listing draft but does not treat it as a final decision. If prohibited wording is present or a required field is missing, the suggestion is not put into effect; the marketplace manager makes the final assessment.

Representative channel content management panel with a work queue, checks and an audit trail: channel listing adaptation queue — **Channel listing adaptation queue** Representative interface — contains no real data. Channel and product names are coded. The panel does not publish listings or send them to a store.

The problem

In day-to-day operations, central product records and channel rules arrive in separate records and files, preventing the team from reviewing the same case in one place.

As a result, the link to the source can be lost while a channel-compliant listing draft is prepared, leading to repeated checks and uncertainty about the basis for the decision.

Incomplete automation may overlook prohibited wording or missing required fields, while poorly controlled automation creates a risk that the listing will be rejected.

What we set out to improve

Time taken for the channel-compliant listing draft to be ready for review
Accurate routing of records with prohibited wording or missing required fields to the correct specialist queue
Recording of suggestions amended or rejected by the marketplace manager

How the system works

01 Retrieve the central product record and channel-rule data from an approved source
02 Verify the source system, record identifier and freshness information
03 Transform the fields into the target process schema
04 Prepare a channel-compliant listing draft
05 Compare the draft with business rules and source records
06 Exception check: prohibited wording is present or a required field is missing
07 Marketplace manager approval, amendment or rejection
08 Write the input, suggestion, amendment and final decision to the audit log

Methods we used

Source-traceable data extraction for the central product record and channel rules
Structured output that restricts the channel-compliant listing fields through business rules
An exception gate that separates records with prohibited wording or missing required fields
A queue that shows the source and suggestion together for the marketplace manager
Duplicate-processing and rollback records to manage the risk of listing rejection

Where people stay involved

The marketplace manager is the final decision-maker. If prohibited wording is present or a required field is missing, the workflow stops and the case is presented to the specialist with the supporting records. The specialist can amend or reject the suggestion, or stop the process.

Data and security

Only the fields required for the task are processed from the central product record and channel rules. Source-system permissions are preserved, and personal and commercially sensitive data is minimised before being passed to the model. Every read, suggestion, human amendment and write to the target system is logged.

Who this suits

A good fit

Teams carrying out repetitive reviews in e-commerce
Companies with defined ownership for sources and approvals
Organisations that want exceptions to remain under human oversight

Not a good fit

When source data is not current
When no decision owner or rollback process has been defined
When the existing method is sufficient for the low volume involved

Frequently asked questions

What data is used?

The central product record and channel rules are used. The exact connections, fields and retention limits are defined during the access review.

How are exceptions handled?

If prohibited wording is present or a required field is missing, the workflow stops. The record enters the marketplace manager's queue with source evidence.

How is poorly controlled automation limited?

Because the listing could be rejected, no final action is taken without human approval. The source, suggestion and human decision are recorded separately.

Project led by:DijitalPi

✦ PI ASSISTANT · ARTIFICIAL INTELLIGENCE

online

Ask the DijitalPi AI Assistant your question

No need to fill in a form and wait for a reply — write your question and let Pi, trained on DijitalPi's 20 years of know-how, answer within seconds.

Instant answers, 24/7
Service-specific context — no generic replies
Can connect you to a free consultation if you wish

Hi! 👋 I'm Pi — DijitalPi's AI assistant. Write whatever you'd like to know about AI System for Adapting Product Listings to Marketplace Rules and I'll answer right away.

Pi Assistant answers are for information purposes; for a proposal get in touch.

ASK AI ABOUT DIJITALPI

Let an AI explain what DijitalPi does.

Opens your chosen assistant with a ready research prompt. It reads the site live and answers.

ChatGPT Claude Gemini Grok Perplexity