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RSRANJEET SAINI

AI business idea · Wholesale & Distribution

AI Product Catalogue Normalisation for Distributors

Clean, merge and enrich product data from hundreds of supplier price lists into one consistent catalogue for e-commerce and ERP systems.

Status: ConceptComplexity: Medium to High

Problem

Distributors receive supplier catalogues in inconsistent spreadsheets and PDFs; teams spend weeks mapping fields and units, delaying listings and causing pricing errors.

Solution

Ingest supplier files, map columns and units to a master schema, deduplicate products, generate consistent descriptions and attributes, and push to ERP or storefront with change tracking.

Target customer

B2B distributors and marketplaces handling 10,000+ SKUs from many suppliers.

Role of technology / AI

Language models for schema mapping, entity matching and description generation; rules for pricing and unit validation.

Business model

Subscription by SKU volume plus onboarding services.

MVP scope

Spreadsheet ingestion, column and unit mapping with review, deduplication for one category, export.

Technology stack

Data pipeline, foundation model API, matching algorithms, PostgreSQL, web review UI.

Opportunity

Clean product data unlocks faster listings and fewer errors; the problem grows with every new supplier.

Risks and challenges

Highly variable supplier data; integration with legacy ERPs; long-tail categories.

This is a concept shared for discussion. It is not a validated business and no outcome is guaranteed. Last updated 11 September 2026.

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