The Foundation for Everything Next

An industrial distributor wanted to automate quoting, ordering and customer service, but every one of those plans ran into the same wall. Its product data was spread across nine sources (an ERP, a CRM, spreadsheets and supplier catalogs) that never agreed with each other.

Infoniq AI built the layer underneath: one normalised database in the client's own cloud, a permanent ID for every product, and a sync that keeps it current. It is the base every system the business wants next is built on, starting with an internal quoting tool.

Data sources unified into one product master

9 → 1

Measured match precision

94–96%

The same part carried a different number in every catalog, and the specs that mattered were buried in free text. Matching a customer's request to the right product depended on who you asked.

Any automation or AI tool built on top would inherit that mess. Before the business could build anything new, the data had to be something it could trust.

We audited every source, then designed a canonical product model in a secure cloud database behind the client's own sign-in. Products were unified in two stages: exact matches on real cross-reference keys, then attribute matches on size, thread, material and finish. Every original part number is kept, and anything that doesn't match cleanly goes to an exception worklist. Nothing is guessed or silently dropped.

AI is used only where it's safe: it fills blanks, never merges two products, and normalising the entire catalog cost $126 in AI spend. Re-runs are identical, every record shows where it came from, and no change reaches production without the client's sign-off. The result is a foundation ready for what comes next: quoting, enrichment, customer portals and AI assistants that query the catalog directly.