Sideberg is a side-by-side extension and migration platform for S/4HANA Cloud Public Edition. We have moved 1,000+ custom objects to the cloud for global manufacturers — with a 19-hour cutover instead of a multi-day shutdown.
Most transformation programs fail because custom code is rewritten by hand, project by project. Sideberg automates the parts that scale — and keeps your core standard.
Keep S/4HANA standard and upgrade-safe. Your custom logic runs in a parallel extension layer with its own lifecycle.
Tool-led migration with automated analysis, so projects are measured in months instead of headcount.
A traditional migration bills for people. Sideberg bills for outcomes — because the tool does the work a consultant team would do by hand.
| Traditional SI approach | Sideberg | |
|---|---|---|
| Custom code | Manual rewrite, object by object | Automated analysis + migration |
| Team size | Large consultant bench | Small tool-led delivery team |
| Cutover | Multi-day shutdown | 19-hour window |
| Timeline | Typically 12–24 months | 3 months, end to end |
| Core state | Core gets modified over time | Clean core preserved |
Click any case for the full story.
Availability check runs were consuming over seven hours and crashing HANA.
A cross-product system switch with a thousand custom objects in scope.
Full cloud migration with sub-second sync and continuous availability.
We are. Sideberg engagements are sold as fixed scope, fixed timeline and a defined cutover window — with the delivery commitment written into the contract. The tool reduces cost; it does not transfer risk to you.
No. We work with SIs. Sideberg plugs into an existing delivery team and takes on the custom-code analysis and migration work that would otherwise consume consultant hours. Your SI keeps the client relationship.
Custom logic is moved into a side-by-side extension layer rather than rewritten into the core. That keeps S/4HANA standard, makes future upgrades cheaper, and leaves the core clean enough for analytics and AI workloads.
Yes. Historical data can be archived and kept queryable, and Public Cloud can be synced bidirectionally with an on-premise data warehouse. You do not have to give up historical reporting to move to the cloud.
No. Customer data submitted during a migration project is never used to train machine learning models, and it is never shared with third parties.
Send us your system profile and we will tell you what can be automated, what cannot, and what the cutover window would look like.
Email hello@sideberg.com