Skip to content
AI ⇄ ERP

Azure OpenAI to Infor LN integration — real-time data sync

Keep Azure OpenAI and Infor LN in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.

  • SOC 2 and 6 other compliance frameworks
  • POC with real engineers in minutes

Adopted by fast-scaling companies moving mission-critical data in real time

Case study
Migrated from MuleSoft
Case study
Migrated from Celigo
Migrated from Heroku Connect
Migrated from Matillion
Case study
Migrated from Fivetran
Case study
Migrated from Celigo
Why teams connect Azure OpenAI and Infor LN

Ground Azure OpenAI on the customers, suppliers, items, and transactions that live in Infor LN, and write the classifications, scores, and extracted fields Azure OpenAI produces back onto those records in real time.

Azure OpenAI is a read-only source: Stacksync reads its data in real time and delivers it into Infor LN, so Infor LN always reflects the current state of Azure 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 LN 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 Azure 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 LN where the business is run.

Stacksync connects Vector stores, Deployments, Models, Fine-tuning jobs in Azure OpenAI with Service orders, Items, Bills of material, Business partners in Infor LN and keeps the two sides in sync in real time. Service orders, Items, Bills of material, Business partners from Infor LN replicate into Azure OpenAI continuously, so retrieval, classification, and reasoning run against current ERP records instead of last night's extract, and the fields Azure OpenAI generates sync back onto the matching record in Infor LN. 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. Azure 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.

Common use cases

  • 01 Sync the Deployments inventory (model, version, TPM capacity) into Postgres so platform teams track every Azure OpenAI deployment across subscriptions in SQL.
  • 02 Land Fine-tuning jobs with their status, base model, and result Files in a warehouse to power MLOps dashboards without per-viewer API calls.
  • 03 Replicate LN data into a warehouse for production, OTIF, and supply chain reporting.
  • 04 Run a two-way sync of business partners between LN and a CRM so sales and manufacturing share account data.

Common sync patterns

Document extraction round-trip

Purchase orders, invoices, or other documents flow from Infor LN into Azure OpenAI for parsing or classification, and the structured result returns to the record it came from.

ERP records as live context

Customers, suppliers, items, and transactions from Infor LN replicate into Azure OpenAI as they change, so search, retrieval, and reasoning run against current records rather than a periodic extract.

Derived fields back on the record

Categories, scores, or extracted values produced in Azure OpenAI sync onto the matching record in Infor LN, where operations and finance teams see and act on them without leaving the ERP.

What you can sync between Azure OpenAI and Infor LN

Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.

Azure OpenAI objects Infor LN objects How this pairing syncs
Usage and quota Per-deployment TPM/RPM consumption and remaining quota, read from usage endpoints and Azure Monitor for cost and throttling reporting. Production orders Shop-floor work orders synced with MES for execution visibility. Usage and quota is specific to Azure OpenAI and Production orders to Infor LN — each maps to any object or custom field on the other side.
Assistants Persistent assistants (preview) with instructions, tools, and linked files; read as configuration inventory, not authored via sync. Warehouse / inventory Stock positions exposed so external channels reflect real availability. Assistants is specific to Azure OpenAI and Warehouse / inventory to Infor LN — each maps to any object or custom field on the other side.
Vector stores File collections (preview) backing file-search retrieval; read as metadata such as name, file counts, and status. Projects Project structures used in engineer-to-order manufacturing scenarios. Vector stores is specific to Azure OpenAI and Projects to Infor LN — each maps to any object or custom field on the other side.
Deployments Named model deployments (model, version, SKU, assigned TPM capacity) read as a control-plane inventory via Azure Resource Manager; read-only in sync. Service orders Aftermarket service documents synced with field service tools. Deployments is specific to Azure OpenAI and Service orders to Infor LN — each maps to any object or custom field on the other side.
Models Catalog of base and fine-tunable models available per region; read-only reference data used to resolve deployment and fine-tuning targets. Items Manufacturing item masters synced to PLM, MES, and commerce systems. Models is specific to Azure OpenAI and Items to Infor LN — each maps to any object or custom field on the other side.
Fine-tuning jobs Training jobs with status, base model, hyperparameters, and result files; status is polled from queued through succeeded or failed. Bills of material Product structures shared with engineering and planning tools. Fine-tuning jobs is specific to Azure OpenAI and Bills of material to Infor LN — each maps to any object or custom field on the other side.

How changes propagate between Azure OpenAI and Infor LN

Each direction of the sync is driven by what the source system can signal and what the destination accepts — detection, delivery, and expected latency below.

Azure OpenAI Infor LN Interval-based propagation

DetectionStacksync polls Azure OpenAI for changes on an incremental schedule, reading only records changed since the previous pass. Polling: list endpoints plus GET on job IDs for status.

DeliveryEach detected change is written to Infor LN through its API, with automatic retries and rate-limit backoff.

Infor LN Azure OpenAI Interval-based propagation

DetectionStacksync polls Infor LN for changes on an incremental schedule, reading only records changed since the previous pass. Event-style BOD publications through Infor ION where configured.

DeliveryAzure OpenAI does not accept inbound record writes, so this direction carries requests rather than records: Azure OpenAI's output flows back as field updates on the originating Infor LN records.

Rate-limit considerations

  • Azure OpenAI: Per-deployment TPM and RPM limits (about 6 RPM per 1000 TPM), scoped by region and subscription; control-plane ARM calls throttle separately.
  • Infor LN: Subject to the ION API gateway's tenant rate limits in cloud deployments.
What ships with Azure OpenAI ⇄ Infor LN

Connect Azure OpenAI and Infor LN for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure OpenAI–Infor LN connection.

Real-time

Real-time sync

Changes in Azure OpenAI or Infor LN instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure OpenAI or Infor LN data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.

At scale

Event queues

Handle millions of events per minute without losing a single Azure OpenAI or Infor LN record.

Observability

Monitoring

Track your Azure OpenAI ⇄ Infor LN sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between Azure OpenAI and Infor LN.

How the Azure OpenAI and Infor LN connectors work

Azure OpenAI

Integration surface
REST data-plane (inference + authoring) and Azure Resource Manager control-plane
Authentication
API key in the api-key header, or a Microsoft Entra ID bearer token / managed identity
Change detection
Polling: list endpoints plus GET on job IDs for status; no webhooks or change feed. Fine-tuning and batch jobs expose queued/running/succeeded states.
Capabilities
read
Rate limits
Per-deployment TPM and RPM limits (about 6 RPM per 1000 TPM), scoped by region and subscription; control-plane ARM calls throttle separately.

Infor LN

Integration surface
SOAP and REST web services, with standardized BOD exchange through Infor ION in Infor OS deployments
Authentication
OAuth 2.0 via the ION API gateway in cloud deployments; application credentials on premises
Change detection
Event-style BOD publications through Infor ION where configured; otherwise polling
Capabilities
read · write
Rate limits
Subject to the ION API gateway's tenant rate limits in cloud deployments.
How it works

How to connect Azure OpenAI to Infor LN — three steps, no code

Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.

  1. 01

    Connect your apps

    Authenticate Azure OpenAI and Infor LN with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.

    • OAuth 2.0
    • SSH tunnel
    • VPC peering
    Azure OpenAI connected
    Infor LN connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure OpenAI and Infor LN objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.

    • Standard objects
    • Custom objects
    • Auto-schema
    objects · Azure OpenAI ⇄ Infor LN
    Customers 12,480
    Sales Orders 8,213
    Invoices 5,902
    Items 1,344
  3. 03

    Map fields

    Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.

    • Auto-map
    • Type casting
    • Transforms
    Azure OpenAI Infor LN
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
FAQ

Azure OpenAI and Infor LN integration FAQ

SECURITY

Security teams trust Stacksync

As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.

SOC 2 Type II
ISO 27001
HIPAA BAA
GDPR
CCPA
DPF US-EU-UK-CH
→ SECURITY WITH BENEFITS

SSO & SCIM

Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.

Alerts

Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.

Secure connection options

Securely connects to your systems with:

Related integrations

Every pair below is a real-time, two-way sync. Search all 478 integrations available for Azure OpenAI and Infor LN.

Popular · 6 of 478
Coworkers laughing in front of a laptop in a casual office setting

Your last integration took months.
Your next one takes a prompt.