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AI ⇄ Database

Azure OpenAI to Reltio integration — real-time data sync

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

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

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Why teams connect Azure OpenAI and Reltio

Sync the records in Reltio into Azure OpenAI and land its embeddings, classifications, and generated fields back on the same rows, in real time and without a pipeline to maintain.

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

AI systems do not hold customers or invoices the way business apps do. What they hold is derived from your data: the vectors and metadata in a vector store, or the classifications, extracted fields, and generated text a model produces over records it was given. Reltio is where those source records actually live. The bridge between the two is the row itself, since an item in Azure OpenAI and the record in Reltio it describes are two halves of the same thing, and they drift the moment one is updated without the other.

Stacksync syncs Crosswalks, Interactions, Matches (Potential Matches), Activity Log in Reltio with Models, Fine-tuning jobs, Files, Batch jobs in Azure OpenAI in real time. Rows created or changed in Reltio flow into Azure OpenAI so inference and embedding run on current data, and the scores, labels, and generated fields Azure OpenAI produces flow back onto the matching rows in Reltio, mapped field by field. A change on either side appears on the other within seconds, with no extraction job or webhook plumbing to keep alive.

Because matching is by a stable identifier, every row in Reltio stays tied to its AI-side counterpart in Azure OpenAI. Retrieval, enrichment, and generated content always resolve back to the record they came from, so there are no orphaned vectors and no labels describing a version of a row that no longer exists.

Common use cases

  • 01 Land Fine-tuning jobs with their status, base model, and result Files in a warehouse to power MLOps dashboards without per-viewer API calls.
  • 02 Poll Batch jobs into an operational database and fire the next pipeline step when a job's status turns to completed.
  • 03 Push cleansed, deduplicated golden records and survivorship results from Reltio back into CRM and ERP systems so every app works from the mastered record.
  • 04 Sync Relations (affiliations, hierarchies, households) between Reltio and a CRM or graph so account and affiliation structures stay aligned.

Common sync patterns

Keep derived data fresh as sources change

When a row in Reltio is updated or removed, its counterpart in Azure OpenAI is updated or removed too, so nothing in Azure OpenAI describes a record that has since changed or gone.

Backfill once, then stay in step

Load your existing rows from Reltio into Azure OpenAI to build the index or enrichment set, then let ongoing changes sync automatically instead of re-running the whole job.

One record, one identifier

Each item in Azure OpenAI carries the key of the row in Reltio it came from, so results resolve back to the exact record with nothing orphaned or duplicated.

What you can sync between Azure OpenAI and Reltio

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 Reltio objects How this pairing syncs
Assistants Persistent assistants (preview) with instructions, tools, and linked files; read as configuration inventory, not authored via sync. Reference Data (RDM) Managed lookup and reference values (country codes, standardized values, hierarchies); read and updated so downstream systems share consistent reference data. Assistants is specific to Azure OpenAI and Reference Data (RDM) to Reltio — 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. Entities Golden records for each configured entity type (for example Organization, Individual/Contact, Location, or Product); full CRUD via /entities, so records are created, updated, and deleted, and Reltio matches and merges them by survivorship rules. Vector stores is specific to Azure OpenAI and Entities to Reltio — 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. Relations Typed relationships between two entities (affiliations, hierarchies, employment, households); read and written via /relations to keep account hierarchies and affiliation graphs aligned across systems. Deployments is specific to Azure OpenAI and Relations to Reltio — 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. Crosswalks Per-entity references to the source systems and their record IDs; written when loading records so Reltio ties each source contribution to a golden record, and read to trace lineage back to origin systems. Models is specific to Azure OpenAI and Crosswalks to Reltio — 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. Interactions Transactional or event records linked to entities (purchases, visits, activities); read and written via /interactions to enrich profiles and power 360-degree reporting. Fine-tuning jobs is specific to Azure OpenAI and Interactions to Reltio — 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. Matches (Potential Matches) Candidate duplicate pairs produced by match rules; read to review, and resolved with merge, unmerge, or not-a-match actions to control survivorship. Files is specific to Azure OpenAI and Matches (Potential Matches) to Reltio — each maps to any object or custom field on the other side.

How changes propagate between Azure OpenAI and Reltio

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 Reltio 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 Reltio through its API, with automatic retries and rate-limit backoff.

Reltio Azure OpenAI Interval-based propagation

DetectionStacksync polls Reltio for changes on an incremental schedule, reading only records changed since the previous pass. Polling the REST API on updateTime (epoch-ms), for example filter=gt(updateTime,<timestamp>), for entities and relations changed past a stored.

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 Reltio 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.
  • Reltio: Reltio applies per-tenant API throttling and returns HTTP 429 (Too Many Requests) when limits are exceeded; there is no single fixed request-per-second cap published for all tenants, and throttling is tuned per tenant and environment. Large loads and reads use bulk create/update and the asynchronous export/jobs API rather than row-by-row calls.
What ships with Azure OpenAI ⇄ Reltio

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

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

Real-time

Real-time sync

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

No-code + pro-code

Workflow automation

Trigger automated workflows whenever Azure OpenAI or Reltio 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 Reltio record.

Observability

Monitoring

Track your Azure OpenAI ⇄ Reltio 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 Reltio.

How the Azure OpenAI and Reltio 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.

Reltio

Integration surface
Reltio REST API (Data API) — /entities, /relations, /interactions, /activities, plus Match, RDM (reference data), and Data Change Request endpoints; base URL https://{environment}.reltio.com/reltio/api/{tenantId}
Authentication
OAuth 2.0 bearer tokens obtained from Reltio's central auth server (POST https://auth.reltio.com/oauth/token, client-credentials or password grant, application/x-www-form-urlencoded) and sent as Authorization: Bearer <token>; access tokens expire after about 60 minutes and are renewed with a refresh token, and are scoped per API (entities_api, relations_api, interactions_api, configuration_api, graphs_api)
Change detection
Polling the REST API on updateTime (epoch-ms), for example filter=gt(updateTime,<timestamp>), for entities and relations changed past a stored watermark. Reltio has no CDC log external tools consume; separately, Reltio's event streaming can publish entity change events (created, changed, removed) to a customer-configured message queue (Amazon SQS/SNS, Google Pub/Sub, Azure Service Bus, or Kafka), which is a queue feed rather than HTTP webhooks.
Capabilities
read · write
Rate limits
Reltio applies per-tenant API throttling and returns HTTP 429 (Too Many Requests) when limits are exceeded; there is no single fixed request-per-second cap published for all tenants, and throttling is tuned per tenant and environment. Large loads and reads use bulk create/update and the asynchronous export/jobs API rather than row-by-row calls.
How it works

How to connect Azure OpenAI to Reltio — 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 Reltio 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
    Reltio connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the Azure OpenAI and Reltio 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 ⇄ Reltio
    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 Reltio
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

Azure OpenAI and Reltio integration FAQ

SECURITY

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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.

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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:

OAuth 2 SSH Tunnelling SSL certificates IP Whitelisting VPN gateway VPC peering and more

Related integrations

Every pair below is a real-time, two-way sync. Search all 404 integrations available for Azure OpenAI and Reltio.

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