Infor M3 to Openai integration — real-time data sync

Openai is a read-only source: Stacksync reads its data in real time and delivers it into Infor M3, so Infor M3 always reflects the current state of Openai — without exports, scripts, or schedulers.

An AI system does not keep customers, orders, or invoices the way an ERP does. What it keeps is derived: the vectors and metadata in a store, or the classifications, extracted fields, and generated text a model produces over records it was handed. Infor M3 is where those source records actually live, across finance, operations, procurement, and inventory, and that data usually stays behind a strict API with many record types. Whatever Openai produces, whether a category, a risk flag, an extracted value, or an embedding, only earns its keep when it lands back on the record in Infor M3 where the business is run.

Stacksync connects Fine-tuning jobs, Files, Batch jobs, Vector stores in Openai with Customer Orders, Purchase Orders, Manufacturing Orders, Inventory Balances in Infor M3 and keeps the two sides in sync in real time. Customer Orders, Purchase Orders, Manufacturing Orders, Inventory Balances from Infor M3 replicate into Openai continuously, so retrieval, classification, and reasoning run against current ERP records instead of last night's extract, and the fields Openai generates sync back onto the matching record in Infor M3. Mapping is field-level, matching is on identifiers you choose, and Stacksync handles the ERP's API limits and schema drift, so there is no extraction pipeline to build or babysit.

Because every AI-side item carries the key of the record it came from, results always resolve to the right customer, supplier, or transaction. Openai reasons over the business as it actually is within seconds of a change, and the people running operations act on model output where they already work, without exporting a file or logging into a second system.