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Database ⇄ AI

InterSystems IRIS to Openai integration — real-time data sync

Keep InterSystems IRIS and Openai 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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Why teams connect InterSystems IRIS and Openai

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

Openai is a read-only source: Stacksync reads its data in real time and delivers it into InterSystems IRIS, so InterSystems IRIS always reflects the current state of 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. InterSystems IRIS is where those source records actually live. The bridge between the two is the row itself, since an item in Openai and the record in InterSystems IRIS it describes are two halves of the same thing, and they drift the moment one is updated without the other.

Stacksync syncs Globals, Namespaces, Stored Procedures, Tables in InterSystems IRIS with Vector stores, Usage & Costs, Projects & Members, Audit logs in Openai in real time. Rows created or changed in InterSystems IRIS flow into Openai so inference and embedding run on current data, and the scores, labels, and generated fields Openai produces flow back onto the matching rows in InterSystems IRIS, 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 InterSystems IRIS stays tied to its AI-side counterpart in 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 Subscribe to batch.completed and fine_tuning.job.succeeded webhooks so a downstream pipeline step fires the moment an offline-inference or training job finishes.
  • 02 Pull Administration Usage and Costs into a warehouse for FinOps chargeback, per-project budget tracking, and spend-tier planning.
  • 03 Keep reference data consistent between an IRIS-based clinical or financial application and downstream SaaS tools
  • 04 Write enriched or corrected records from SaaS apps back into IRIS tables for on-platform processing

Common sync patterns

Write results back onto the record

Scores, labels, extracted fields, or generated text produced in Openai land on the matching row in InterSystems IRIS, next to the source data your applications already query.

Keep derived data fresh as sources change

When a row in InterSystems IRIS is updated or removed, its counterpart in Openai is updated or removed too, so nothing in Openai describes a record that has since changed or gone.

Backfill once, then stay in step

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

What you can sync between InterSystems IRIS and Openai

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.

InterSystems IRIS objects Openai objects How this pairing syncs
Stored Procedures Server-side logic callable over SQL supports controlled writes and transformations. Vector stores File collections backing file-search retrieval, with name, file counts, usage bytes, and status; read as a metadata inventory of retrieval assets. Stored Procedures is specific to InterSystems IRIS and Vector stores to Openai — each maps to any object or custom field on the other side.
Tables Relational projections of stored data are the primary read/write surface for SQL-based syncs. Usage & Costs Per-model and per-project token, request, and dollar figures from the Administration Usage and Costs endpoints, read for FinOps chargeback and spend reporting. Tables is specific to InterSystems IRIS and Usage & Costs to Openai — each maps to any object or custom field on the other side.
Views SQL views expose curated slices of data for outbound replication. Projects & Members Organization projects, their members, and service accounts from the Administration API; read as an access-and-ownership inventory. Views is specific to InterSystems IRIS and Projects & Members to Openai — each maps to any object or custom field on the other side.
Schemas Schema organization scopes which tables a sync connection can see. Audit logs Organization audit-log events (API-key changes, logins, project edits) from the Administration API; read for compliance and security monitoring. Schemas is specific to InterSystems IRIS and Audit logs to Openai — each maps to any object or custom field on the other side.
Persistent Classes Object-model classes project to tables, so class data is reachable through SQL. Models Catalog of available base, snapshot, and fine-tuned models with owner and capabilities; read-only reference data used to resolve inference and fine-tuning targets. Persistent Classes is specific to InterSystems IRIS and Models to Openai — each maps to any object or custom field on the other side.
Globals The underlying multidimensional storage; typically accessed indirectly via SQL or objects in syncs. Fine-tuning jobs Training jobs with status, base model, hyperparameters, trained-model name, and result files; status received by webhook or polled from queued through succeeded or failed. Globals is specific to InterSystems IRIS and Fine-tuning jobs to Openai — each maps to any object or custom field on the other side.

How changes propagate between InterSystems IRIS and Openai

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.

InterSystems IRIS Openai Interval-based propagation

DetectionStacksync polls InterSystems IRIS for changes on an incremental schedule, reading only records changed since the previous pass. Polling (timestamp or query-based).

DeliveryOpenai does not accept inbound record writes, so this direction carries requests rather than records: Openai's output flows back as field updates on the originating InterSystems IRIS records.

Openai InterSystems IRIS Sub-second propagation

DetectionOpenai notifies Stacksync of record changes through webhook events. Push webhooks (Standard Webhooks spec, whsec_ signing secret) fire on batch.completed, fine_tuning.job.succeeded/failed, response.completed/failed,.

DeliveryEach detected change is applied to InterSystems IRIS as a row-level write, with types converted between the two schemas.

Rate-limit considerations

  • InterSystems IRIS: Constrained by database resources rather than published API rate limits.
  • Openai: Rate limits are set per organization and per project as RPM/RPD and TPM/TPD and rise across five spend-based usage tiers; responses carry x-ratelimit-remaining headers and return HTTP 429 on breach.
What ships with InterSystems IRIS ⇄ Openai

Connect InterSystems IRIS and Openai for flexible, real-time data sync.

Real-time sync, workflow automation, event queues, EDI, and monitoring, for every InterSystems IRIS–Openai connection.

Real-time

Real-time sync

Changes in InterSystems IRIS or Openai instantly reflect in both systems. No stale data, no manual imports.

No-code + pro-code

Workflow automation

Trigger automated workflows whenever InterSystems IRIS or Openai 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 InterSystems IRIS or Openai record.

Observability

Monitoring

Track your InterSystems IRIS ⇄ Openai sync health, view errors, and replay failed events in one click.

Trading partners

EDI

Transform legacy EDI complexity into simple database interactions between InterSystems IRIS and Openai.

How the InterSystems IRIS and Openai connectors work

InterSystems IRIS

Integration surface
SQL over JDBC/ODBC, plus object and REST access layers
Authentication
Database credentials
Change detection
Polling (timestamp or query-based); no standard webhook surface
Capabilities
read · write
Rate limits
Constrained by database resources rather than published API rate limits

Openai

Integration surface
REST API: data-plane inference and authoring (api.openai.com/v1) plus the Administration API (/v1/organization/*) for usage, costs, projects, and audit logs
Authentication
Bearer API key scoped to a project or user (sk-...) in the Authorization header, with optional OpenAI-Organization and OpenAI-Project headers; the Administration API requires an Admin key (sk-admin-...)
Change detection
Push webhooks (Standard Webhooks spec, whsec_ signing secret) fire on batch.completed, fine_tuning.job.succeeded/failed, response.completed/failed, and eval.run events; objects without a webhook are read by list plus GET-by-ID. No row-level CDC feed.
Capabilities
read · webhooks
Rate limits
Rate limits are set per organization and per project as RPM/RPD and TPM/TPD and rise across five spend-based usage tiers; responses carry x-ratelimit-remaining headers and return HTTP 429 on breach.
How it works

How to connect InterSystems IRIS to Openai — 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 InterSystems IRIS and Openai 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
    InterSystems IRIS connected
    Openai connected
    OAuth 2.0
    SSH tunnel
    SSL certificate
    VPC peering
  2. 02

    Choose tables

    Pick the InterSystems IRIS and Openai 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 · InterSystems IRIS ⇄ Openai
    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
    InterSystems IRIS Openai
    Company company_name text
    Email email text
    Amount amount numeric
    Created created_at timestamp
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FAQ

InterSystems IRIS and Openai 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.

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→ 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:

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 440 integrations available for InterSystems IRIS and Openai.

Popular · 7 of 440
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