Connect Databricks and
Oracle Retail with AI

Redbird AI syncs retail operational data from Oracle Retail into Databricks for ML and analytics, then pushes forecasts, pricing models, and inventory insights back into merchandising and planning workflows. Stop manually exporting data, running batch jobs, and reconciling predictions across systems.

No code required
Live in minutes
SOC 2 Type II

What you can automate today

Redbird gives your team ready-to-run workflows — just connect your accounts and go.

Sync Oracle Retail inventory snapshots into Databricks Delta tables for ML training

Automatically pull inventory positions, SKU movements, and stock levels from Oracle Retail into Databricks feature stores. Keep training data fresh for demand forecasting and replenishment models. Trigger retraining pipelines when new data arrives.

Push Databricks demand forecast outputs into Oracle Retail planning modules

Write ML-generated demand forecasts from Databricks directly into Oracle Retail's merchandise planning and replenishment systems. Replace manual forecast uploads with automated pipeline writes. Ensure planners work from the latest model outputs.

Enrich Oracle Retail transactional data with customer and market features from Databricks

Join point-of-sale and inventory transactions from Oracle Retail with customer segments, location intelligence, and external market signals stored in Databricks. Build unified retail analytics datasets that combine operational and analytical context.

Automate markdown optimization by syncing Databricks pricing models into Oracle Retail

Deploy price elasticity and markdown optimization models from Databricks into Oracle Retail merchandising workflows. Automatically update recommended pricing and promotion strategies based on real-time inventory and sales velocity signals. Eliminate spreadsheet-based pricing decisions.

Alert merchandising teams when Databricks detects anomalies in Oracle Retail inventory data

Run anomaly detection and forecast accuracy models in Databricks on Oracle Retail inventory and sales data. Trigger alerts when models detect stockouts, overstock risk, or demand pattern shifts. Route alerts to the right planning teams with context.

Archive Oracle Retail historical data into Databricks lakehouse for long-term analytics

Continuously sync completed sales, fulfillment, and planning transactions from Oracle Retail into Databricks for compliance and historical analysis. Maintain a unified retail data archive across merchandising, supply chain, and store operations. Enable multi-year trend analysis without taxing Oracle Retail production systems.

Live in four steps

No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.

01

Connect your accounts

Authorize Databricks and Oracle Retail with OAuth or API credentials. Redbird never stores your data — it just passes through.

02

Describe what you want

Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.

03

Review and activate

Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.

04

Let it run — and iterate

Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.

Built for data-driven teams

Redbird AI understands both Databricks lakehouse schemas and Oracle Retail's merchandising, inventory, and planning data models — mapping SKUs, locations, hierarchies, and forecast structures between systems.

AI that maps retail operations to analytics workflows

Redbird automatically recognizes Oracle Retail entities like item masters, inventory positions, purchase orders, and assortment plans, then maps them to Databricks Delta tables, feature stores, and ML pipelines. The platform understands retail hierarchies, location structures, and time-series formats, so you don't manually join product IDs, normalize date ranges, or reconcile store codes. Changes to Oracle Retail schemas or Databricks table structures are detected and adapted without breaking pipelines.

SKU and item master mapping
Inventory position normalization
Forecast schema alignment
Retail hierarchy translation
10×

faster than building custom integrations between Databricks and Oracle Retail

No custom Spark jobs, API wrappers, or manual schema mapping required

Auto-generated reports

Redbird can pull from Databricks and Oracle Retail simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.

Trigger-based alerts

Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Databricks or Oracle Retail.

Enterprise-grade security

SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.

Bidirectional sync

Push data from Databricks into Oracle Retail, or from Oracle Retail back into Databricks. Resolve conflicts with configurable merge rules.

Full audit trail

Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.

Triggers & actions for every team

Start automations from any event in Databricks or Oracle Retail — new data, model runs, inventory changes, or planning updates.

Databricks
Triggers & Actions
Trigger

ML model completes training run

Trigger when a Databricks model training job finishes and new predictions are ready for deployment.

Trigger

Delta table receives new batch

Start workflows when fresh data lands in a Databricks Delta table or feature store.

Trigger

Scheduled job execution

Trigger actions when a Databricks notebook or pipeline runs on schedule.

Action

Write prediction results to Delta table

Push forecast outputs, segmentation results, or model scores into Databricks tables for downstream use.

Action

Trigger MLflow model deployment

Automatically deploy updated models to Databricks serving endpoints or feature stores.

Action

Execute Databricks notebook

Run transformation, analysis, or model inference notebooks in response to Oracle Retail data changes.

Oracle Retail
Triggers & Actions
Trigger

Inventory position updated

Start workflows when stock levels, allocations, or availability change in Oracle Retail systems.

Trigger

Merchandise plan finalized

Trigger when assortment plans, buy quantities, or seasonal planning is completed and approved.

Trigger

Sales transaction recorded

Respond to new point-of-sale, return, or fulfillment transactions as they occur.

Action

Update demand forecast values

Write ML-generated forecasts directly into Oracle Retail planning and replenishment modules.

Action

Create or update pricing recommendations

Push optimized pricing, markdown strategies, or promotion plans into Oracle Retail merchandising systems.

Action

Sync inventory adjustments

Write inventory corrections, reallocation suggestions, or stock transfers back to Oracle Retail.

Databricks
+
Oracle Retail

Ready to connect your stack?

Sync Databricks and Oracle Retail in minutes. Stop exporting CSVs, building custom Spark jobs, or manually updating forecasts. Let Redbird AI handle the data work so your team can focus on better merchandising and planning decisions.

Get started → Book a demo