AI-Powered Data Transformation

Your spare parts data is costing you money.
We fix it.

Duplicates. Inconsistent naming. Missing classifications. It all adds up to excess inventory, failed searches, and wrong parts ordered. Our AI-powered platform transforms your messy master data into clean, standardized records.

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restrktur_transform.sh
Input: Raw Customer Data
brg ball 6205-2RS,SKF,,ea,
SEAL KIT FOR VLV,fisher,,pc,
3M MINNESOTA MINING,Scotch-Weld,,each,
pump cntrifugal,FLOWSERVE CORP,,1,
Processing with AI classification engine...
Output: Cleaned & Classified
BEARING BALL 6205-2RS, SKF (PIW3FZK), NMQ: BEARING/BALL, SPARE_PART
SEAL KIT FOR VALVE, FISHER (N59MX3F), NMQ: KIT/SEAL, KIT
ADHESIVE DP810, 3M (9U9QY33), NMQ: ADHESIVE/ANY, CONSUMABLE
PUMP CENTRIFUGAL, FLOWSERVE (AX9AWZA), NMQ: PUMP/CENTRIFUGAL, EQUIPMENT
16,500+
Manufacturers Mapped

Comprehensive manufacturer database with canonical name resolution

30,500+
Name Variants Resolved

PARKER has 68 aliases, ABB has 56, EMERSON has 38 — we know them all

1,800+
Part Classifications

NMQ taxonomy covering every industrial spare part category

The Hidden Cost of Bad Data

Every maintenance team knows the pain. Your ERP is full of records that nobody can find, duplicates that inflate inventory, and descriptions that could mean anything.

Duplicates

Same part, 12 different records. Each site orders their own, inventory balloons.

Inconsistent Naming

"BRG", "BEARING", "BRNG" — same thing, impossible to search.

Missing Classifications

No taxonomy means no reporting, no spend analysis, no strategic sourcing.

Wrong Part Types

Is it equipment or a spare part? Most MDM vendors can't tell you. We can.

Built for Heavy Industry

We understand the unique data challenges of asset-intensive industries. Our reference data is built from real-world industrial catalogs.

Oil & Gas
Mining
Power Generation
Manufacturing
Water & Utilities

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