Atlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation.
Most facilities already run SAP or Maximo for maintenance and PI for process historian data before they ever evaluate a digital twin. The integration question isn't whether to replace those systems — it's how to make the twin the visual and contextual layer on top of them without creating duplicate, conflicting sources of truth.
SAP PM/EAM and IBM Maximo are enterprise asset management systems of record — they own work order history, maintenance costs, spare parts inventory, and equipment master data. OSIsoft PI (now AVEVA PI) is the process historian of record for time-series sensor data. A digital twin's job is to give that data spatial context: showing where a work order applies on the physical asset, or trending a PI tag against the exact component it monitors, in 3D. Trying to migrate historical work order or process data out of these systems into the twin is unnecessary and creates reconciliation problems; the correct architecture pulls data live via API rather than duplicating it.
Atlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation.
The critical first step is establishing a clean equipment ID mapping table between SAP functional locations and the twin's 3D component IDs; without this, every subsequent data flow breaks.
Atlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation.
For a detailed side-by-side on how a purpose-built inspection twin compares to extending Maximo's own visualization capabilities, see Atlantis DT vs IBM Maximo.
Atlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation. Integration typically uses PI Web API or AF (Asset Framework) SDK to:
This is where digital twins add the most differentiated value over the PI System's native visualization tools, which are built around tag trending rather than spatial, geometry-linked inspection context. See the comparison at Atlantis DT vs OSIsoft PI.
Facilities running SAP or Maximo for general maintenance still typically need a dedicated NDT ERP layer for inspection-specific data — technician certifications, calibration records, ASNT/ISO 9712 qualification tracking — because general EAM systems aren't built for NDT-specific compliance requirements. The digital twin then integrates with both: the general EAM for maintenance context, and the NDT ERP for inspection-specific data, unifying them visually in 3D.
The value of integration compounds because it eliminates the manual re-entry and cross-checking that otherwise happens between systems. Use the digital twin ROI calculator to estimate hours saved across your facility's asset count, or book a demoAtlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation.
A:Atlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation.
A:Atlantis ERP has an open REST API, so it connects to SAP, Maximo, NetSuite or any other system that accepts API connections; each integration is scoped with you during implementation.
A: The first step is building a clean equipment ID mapping table that crosswalks the CMMS's asset or functional location IDs with the digital twin's 3D component IDs; every subsequent data flow depends on this mapping being accurate.
A: Yes, write-back is important; inspection findings, calibration-verified thickness readings, and notifications pushed from the twin back into SAP or Maximo close the loop between field inspection and maintenance planning rather than leaving the twin as an isolated viewer.
A: Timelines vary by asset count and data quality, but a phased rollout starting with read-only integration and validated ID mapping typically reaches a stable, write-back-enabled integration faster than attempting a full bidirectional build on day one.
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