ATOM Data Lab generates your actual target-system load files from raw extracts, puts real data in front of your experts, and turns every fix into a rule that sticks. Built by a consultancy that runs it on live SAP to SyteLine and SAP to D365 migrations.
A method of ERP data migration in which the actual target-format load file is generated first, from raw source extracts, and becomes the surface where experts review, fix, and approve real data.
Opposed to: mapping-spreadsheet migration, where experts approve abstractions and the truth arrives at mock load three.
Read why we work this way →Push a file a human already built into the target.
Pipe data between live systems.
Dedupe one domain, then hand you a spreadsheet.
ATOM builds the load file itself, from raw extracts, and makes it the thing your experts approve.
ATOM’s AI reads your extracts, proposes the joins, maps every column, and regenerates on demand. It cannot release a file. Release is a human-only gate, enforced in the platform, and every action, AI or human, lands in the same immutable audit log. Autonomous where that’s fast. Governed where it counts.
Extracts in, released load file out. Every fix becomes a rule, every approval travels with the data, and re-review shrinks each cycle.
See how it works →Every number below is qualified. We’d rather under-claim.
You bid the data workstream fixed fee. Then every mock load finds what the last one missed, and the rework comes out of your margin. ATOM captures every correction as a rule, so each mock load starts where the last one ended. Your senior people spend their hours on decisions clients pay for, not on spreadsheet repair.
The people who build ATOM run it on live cutovers. Inside your project, every decision persists as a rule. What each engagement teaches us about an ERP corridor ships back into the platform itself. Every project improves the product. We are the consultants, and this is our tool. If it breaks, our projects break first.
Each implementation discovers business rules, resolves exceptions, and delivers a clean cutover.
Each one also hardens the platform itself: corridor knowledge, validations, and method that make the next migration faster.
Every column ships with a confidence score, a plain-English explanation, and real sample rows. Nothing releases without a human verdict, and every decision, AI or human, lands in the same immutable audit log.
Everyone’s is. The difference is where the mess surfaces: in iteration one, in target format, where every fix becomes a rule instead of tribal knowledge.
Scoped to your project, isolated per project on every request, fail-closed. The full answer lives on the security page.
No. It replaces their spreadsheets. Your experts review real data, your integrator owns the load, and both get better artifacts to work with. See partners.
Templates, dictionaries, and rules are data, not code. New corridors onboard without re-engineering.
The extract challenge: 45 minutes, your data, no slideware.
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