Newboot Genesis use case · ERP Migration

Migrate your ERP to SAP S/4HANA or any target, with a map of your data, not a guess.

With mainstream maintenance of SAP ECC ending in 2027, many companies are planning their move. Newboot Genesis maps your source ERP (SAP, Oracle, Microsoft Dynamics or in-house), tests the migration rules on your real data and generates the transformation scripts, with the lineage of every value.

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Data Fingerprint · SAP ECC → S/4HANAMapped

SourceBusiness objectTarget

KNA1, KNVVCustomerBusiness Partner

MARA, MARCProductProduct master

LFA1SupplierBusiness Partner

Z_PRICE_TABPrice conditionRule to review

Illustrative view

How it works

Understand, map, transform.

Source systemsSAP ECC, Oracle, Dynamics, files

Data FingerprintStructures and quality, discovered automatically

Ontology and lineageNewboot Genesis

Harmonized targetSAP S/4HANA or any target

Faster, better-controlled migrations

Structures, quality issues and dependencies are known before the first transformation.

Lineage you can audit

Every target value traces back to its source and to the rule that produced it.

Generated transformation logic

The model is the spec: Genesis produces SQL, DAX or Python to move data between systems.

A reusable foundation

The ontology stays after go-live and serves the next IT projects and AI agents.

Built on Newboot Genesis

A living map of your data, generated from your systems.

Genesis connects to ERPs, BI tools, databases and files, and describes what every value means, which rules apply and where it comes from. Teams and AI agents then work on explained data instead of raw tables.

up to −65%tokens sent to the LLM, thanks to described data (Newboot R&D estimate)

MCPserver that serves the map to any AI agent

Azuredeployment inside your own tenant

Discover the Newboot Genesis platform →

FAQ

Questions from IT teams.

Is it only for SAP?

No. Genesis works on SAP ECC and S/4HANA, Oracle, Microsoft Dynamics, in-house ERPs, databases and files, for migrations as well as harmonizations between systems.

Can we test the migration before go-live?

Yes. Rules are simulated on your real data: you see which rows pass and which are blocked, and why, before anything is loaded into the target.

Does it replace our integrator?

No. It gives your integrator and your teams a shared, governed map of the data, which shortens analysis and reduces errors.

Where does it run?

Inside your perimeter, on-premise or in your own Azure tenant.

Newboot Genesis

Other use cases on the same platform.

Power BI SimulatorRun “what-if” scenarios in plain language on top of your existing dashboards.Talk-to-DataGive teams and AI agents sourced, auditable answers from governed data. All use casesFinance, supply chain, sales, retail, M&A, ESG and manufacturing.

Next step

Start with one system and one question.

We connect to one source, generate its ontology and show you what it reveals about your data, in a scoping workshop.

1
Scoping workshopIdentify the priority use case and the data available.
2
PilotProve the value on one line, one site or one IT scope.
3
Deploy and replicateIndustrialize, then roll out to other lines and sites on the same foundation.