Real-time sync
Changes in Azure OpenAI or Orderful instantly reflect in both systems. No stale data, no manual imports.
Keep Azure OpenAI and Orderful in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Azure OpenAI is a read-only source: Stacksync reads its data in real time and delivers it into Orderful, so Orderful always reflects the current state of Azure OpenAI — without exports, scripts, or schedulers.
Azure OpenAI works on data it does not own. The records, conversations, tickets, messages, and events it needs to embed, classify, summarize, or answer questions about actually live in Orderful, the tool the team uses every day. So the value of Azure OpenAI depends on two flows that most teams stitch together with a custom script or a one-time export: getting Orderful's data in, and getting the model's results back out to where people can act on them. When either flow runs on a batch or a stale snapshot, the model reasons over yesterday's data and its output never reaches the record it belongs to.
Stacksync syncs Relationships, Validation guidelines, Acknowledgments, Webhook events from Orderful into Azure OpenAI continuously, so the model always works from current records instead of a snapshot, and writes Usage and quota, Assistants, Vector stores, Deployments, the scores, labels, summaries, drafts, and embedding metadata Azure OpenAI produces, back onto the matching record in Orderful. The sync is field-level and keyed on a stable identifier, so every output attaches to the exact record it came from and each system keeps its own extra fields untouched.
You decide the direction and the trigger conditions per field: pull records one way to build and keep a retrieval corpus current, push results the other way onto the operational record, or both.
As records change in Orderful, the synced copy in Azure OpenAI updates within seconds, so retrieval and generation reason over live data rather than a stale export.
Categories, sentiment, priority, or scores produced by Azure OpenAI write back onto the matching record in Orderful, so the team acts on them in the tool they already use.
Summaries, suggested replies, or generated content from Azure OpenAI sync onto the Orderful record as a field or note, ready for a person to review before it goes out.
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 | Orderful objects | How this pairing syncs | |
|---|---|---|---|
| Fine-tuning jobs Training jobs with status, base model, hyperparameters, and result files; status is polled from queued through succeeded or failed. | Trading partners The retailers, carriers, and suppliers a company exchanges documents with | Fine-tuning jobs is specific to Azure OpenAI and Trading partners to Orderful — each maps to any object or custom field on the other side. | |
| Files Uploaded training, validation, and batch-input files plus generated output files; listed and read by ID, not written back in sync. | Relationships Active partner connections per transaction type that govern what can be sent and received | Files is specific to Azure OpenAI and Relationships to Orderful — each maps to any object or custom field on the other side. | |
| Batch jobs Asynchronous bulk-inference jobs; status and output-file IDs are polled to completion to drive downstream pipeline triggers. | Validation guidelines Partner-specific rules transactions are checked against before delivery | Batch jobs is specific to Azure OpenAI and Validation guidelines to Orderful — each maps to any object or custom field on the other side. | |
| Usage and quota Per-deployment TPM/RPM consumption and remaining quota, read from usage endpoints and Azure Monitor for cost and throttling reporting. | Acknowledgments 997 functional acknowledgments confirming receipt of transmitted documents | Usage and quota is specific to Azure OpenAI and Acknowledgments to Orderful — 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. | Webhook events Push notifications for inbound documents and transaction status changes | Assistants is specific to Azure OpenAI and Webhook events to Orderful — 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. | Transactions EDI documents such as 850 purchase orders, 810 invoices, and 856 ship notices, represented as JSON | Vector stores is specific to Azure OpenAI and Transactions to Orderful — each maps to any object or custom field on the other side. |
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.
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 Orderful through its API, with automatic retries and rate-limit backoff.
DetectionOrderful notifies Stacksync of record changes through webhook events. Webhooks push inbound transactions and status events.
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 Orderful records.
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Azure OpenAI–Orderful connection.
Changes in Azure OpenAI or Orderful instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Azure OpenAI or Orderful data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Azure OpenAI or Orderful record.
Track your Azure OpenAI ⇄ Orderful sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Azure OpenAI and Orderful.
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.
Authenticate Azure OpenAI and Orderful with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Azure OpenAI and Orderful 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.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time integration between Azure OpenAI and Orderful — Azure OpenAI is a read-only source, so data flows from it into the other system: authenticate both systems, choose the objects to sync, map fields visually, and changes propagate in milliseconds — no code required.
Yes — Stacksync ships production-grade connectors for both Azure OpenAI and Orderful. The connectors handle authentication, schema detection, rate limits, and retries; you configure the sync, and Stacksync operates it.
Change detection on Azure OpenAI: 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. On Orderful: Webhooks push inbound transactions and status events; polling available as fallback. Each detected change propagates to the other side in milliseconds, with field-level conflict resolution and an inspectable event log.
On the Azure OpenAI side: Usage and quota, Assistants, Vector stores, Deployments, plus custom fields where Azure OpenAI exposes them. On the Orderful side: Relationships, Validation guidelines, Acknowledgments, Webhook events. Stacksync auto-detects both schemas and converts types between the two systems.
Azure OpenAI is a read-only source, so this integration runs one-way: Stacksync reads from Azure OpenAI in real time and delivers into Orderful. Field mapping and monitoring work the same as for two-way pairs.
Common patterns for Azure OpenAI and Orderful: Keep the model's knowledge current; Where Azure OpenAI classifies or scores: results land on the record; Where Azure OpenAI generates text: drafts and summaries where the work happens. As records change in Orderful, the synced copy in Azure OpenAI updates within seconds, so retrieval and generation reason over live data rather than a stale export.
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.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 369 integrations available for Azure OpenAI and Orderful.