OpusGo
Integrate with yourSAP B1
AI

How AI maps ERP data to an online store

June 1, 2026 · 6 min read · OpusGo team

Quick answer

An AI translation layer reads the ERP's actual schema - tables, fields, custom extensions - and infers how each element maps to store concepts like products, prices and orders. It generates the transformations a consultant would hand-write, validates them against real records, and re-maps automatically when the schema changes.

Live sync
<2s latencytwo-way24/7
SAP B1pricing - stock
Dynamics 365customers
NetSuiteorders
AI Translation Engine
maps - transforms - syncs - self-heals
Online storereal-time
B2B portalcontract pricing
Marketplacesorders back
Sales order #2841 created in SAP B1just now
Price list B2B-Gold pushed to store2s ago
Stock synced across 4 warehouses5s ago
Invoice INV-1180 visible in portal8s ago
OpusNext

Every ERP, fluent in commerce.

The problem with manual mapping

Classic integration is a spreadsheet: ERP field on the left, store field on the right, a consultant in the middle. It is slow, priced per field, and frozen in time - the day someone adds a custom field or a new price list, the spreadsheet is wrong and the connector silently drops data.

What the AI actually does

The engine introspects the live schema: standard objects, custom fields, units of measure, price list structures. It infers intent from names, types and the data itself - a field full of warehouse codes maps differently than one full of EANs - and proposes a complete mapping with transformations, which is validated against thousands of real records before anything goes live.

Self-healing, defined

When the ERP changes - a patch renames a table, an admin adds a field - the engine detects the drift, regenerates the affected mappings and revalidates. What used to be a support ticket and a consulting invoice becomes a log entry.

Where humans stay in the loop

Mapping proposals are reviewable, business rules are confirmed not guessed, and changes to money-touching flows - pricing, credit - can be gated behind approval. The AI removes the labor, not the control.

Key takeaways

  • AI infers mapping from the real schema, custom fields included
  • Proposals are validated on real records before go-live
  • Schema drift triggers re-mapping, not support tickets
  • Humans approve; the AI does the labor

Frequently asked questions

Is AI mapping reliable enough for pricing data?+

Mappings are validated against real records and money-touching flows can require human approval - in practice this is more reliable than a hand-maintained spreadsheet.

What happens when my ERP gets a patch?+

The engine detects schema changes, regenerates affected mappings and revalidates them - the self-healing behavior that distinguishes AI layers from static connectors.

Does this replace integration consultants?+

It replaces the field-by-field labor. Scoping, business rules and process decisions still benefit from people who know your operation.

See it on your own ERP.

Book a demo - we will connect your ERP live.

Book a demo