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HOW IT WORKS

The Load-File-First Loop.

Six steps around one artifact. The file card on the right is the same file, start to finish; watch what happens to it as you scroll.

Six steps around one artifact. Each step shows the same file at that moment in the loop.

01

Hand off extracts.

Raw table dumps from the source system, as-is. No separate pre-cleansing project: cleansing decisions happen inside the review loop, where each one persists as a rule.

02

ATOM Data Lab assembles the file.

The AI proposes the joins and maps every column into the target template, each with a confidence score and a plain-English explanation. Seconds for standard files.

MARA left join MARC on MATNR + WERKS, language = EN
03

Your experts review the real file.

Real parts, vendors, orders, in the new system’s format, column by column, with sample rows. A rejection is a rejection of visible bad data, not a theory.

04

Fixes become rules.

Every correction persists: transforms, crosswalks, defaults. Mock load three starts where mock load two ended.

05

Carry forward and iterate.

Approvals travel with the data via column fingerprints. On a typical re-release, roughly 77% of columns need no re-review.

06

Release and load.

Release is a human-only, audited gate. Your integration partner sees every release in a dedicated portal the moment it clears review, and pulls each file as your experts sign it off.

And your new ERP’s built-in loader? It consumes finished load files; it doesn’t build them, review them, or remember your fixes. ATOM is how the file gets built and approved. The built-in loader is the last step, and we hand it a file that already cleared your experts.

YOUR FIRST TWO WEEKS

A typical first cycle. Qualified, like every number we publish.

DAY 1
Hand off raw extracts, as-is.no pre-cleansing project
FIRST DAYS
First files generated in the target format.validation and health scoring on the first generation
WEEK ONE
Your experts are reviewing real parts and vendors, column by column.typical first cycle, not guaranteed

Traditional projects find data problems at mock load three. ATOM puts them in front of your experts in iteration one.

with validation and health scoring on the first generated file

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