Skip to content
Northstone Insights

Service

Your product data is real. It's just not usable yet.

Datasheets, catalogs, spreadsheets, and manufacturer PDFs contain everything AI needs to understand your products, but not in a form it can read. Product & Technical Data Transformation converts fragmented product information into structured, AI-ready data, SKU by SKU.

Request a data sample assessment

Why this matters

Business problems we solve

Specifications are trapped in unstructured documents

PDFs, scanned datasheets, and manufacturer catalogs hold the specifications your products need to be found and compared by, but none of it is queryable, searchable, or usable by AI in that format.

Large SKU portfolios make manual structuring impractical

With thousands of SKUs across multiple manufacturers, manually re-entering specifications, compatibility data, and attributes isn't realistic, but leaving it unstructured means AI can't use any of it.

Product matching and substitution rely on tribal knowledge

Knowing which products are compatible, equivalent, or valid substitutes for a discontinued item usually lives in one or two people's heads, not in any system.

What we do

Capabilities

Document extraction and parsing

We extract specifications, dimensions, compatibility data, and attributes from PDFs, datasheets, and scanned catalogs at scale.

Attribute normalization

We standardize units, naming conventions, and attribute structures across manufacturers so products can actually be compared and searched.

Product relationship mapping

We map compatibility, equivalence, and substitution relationships between SKUs so matching and substitution logic can be automated, not guessed.

Structured catalog output

We deliver the transformed data into your PIM, ERP, or a structured format ready for AI search, product matching, and downstream automation.

How we work

Methodology

  1. 1

    Inventory

    Catalog every source of product and technical data — PDFs, spreadsheets, manufacturer feeds, and existing systems.

  2. 2

    Extract and normalize

    Pull specifications and attributes out of unstructured documents and standardize them into a consistent structure.

  3. 3

    Map relationships

    Identify compatibility, equivalence, and substitution links between products.

  4. 4

    Deliver

    Load the structured data into your systems, or a standalone structured catalog ready for AI use.

Deliverables

  • Structured product and specification database
  • Normalized attributes and units across manufacturers
  • Product compatibility and substitution mapping
  • Data delivered into your PIM/ERP or as a standalone structured catalog

Benefits

  • Products become searchable and comparable by specification, not just by name
  • Product matching and substitution stop depending on one person's memory
  • Technical enquiries get answered from structured data, not a PDF search
  • A structured foundation ready for AI search, quoting, and automation

Who this is for

Distributors and manufacturers with large, multi-manufacturer SKU portfolios where specifications currently live in PDFs, spreadsheets, and catalogs rather than structured systems.

See what your product data looks like structured.

We'll assess a sample of your catalogs, datasheets, or spreadsheets and show you what structured output looks like.

Request a data sample assessment