Sync customer behavior data, product performance metrics, and ML predictions between your data lakehouse and commerce platform. Stop manually exporting order data for analysis or building custom ETL pipelines to power personalization.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically capture order transactions, cart events, and customer session data from Commerce Cloud into your Databricks lakehouse. Build a complete view of customer behavior without manual data exports or batch uploads.
Train recommendation and propensity models in Databricks, then automatically push prediction scores to Commerce Cloud for real-time product recommendations. Update customer segments and affinity scores as new data arrives.
Surface lifetime value scores, churn predictions, and behavioral segments calculated in Databricks directly in Commerce Cloud customer records. Enable merchandising teams to personalize experiences using advanced analytics without querying raw data.
Run anomaly detection models on Commerce Cloud product metrics in Databricks, then automatically notify teams when conversion rates drop or inventory turns spike. Include context from sales trends and customer segments in alerts.
Automatically move aged order history, product catalog versions, and promotion performance data from Commerce Cloud to your Databricks lakehouse. Maintain compliance and enable multi-year trend analysis without bloating production systems.
Merge real-time Commerce Cloud sales performance with Databricks demand forecasting and inventory optimization models. Automatically distribute reports showing which products need restocking, repricing, or promotional support.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Databricks and Salesforce Commerce Cloud with OAuth or API credentials. Redbird never stores your data — it just passes through.
Tell Redbird what to do in plain language — no SQL, no code, no configuration files required.
Redbird shows you exactly what it will do before running anything. Approve the workflow, set a schedule, and switch it on.
Workflows run on your schedule or on triggers. Every run is logged. Adjust with natural language at any time.
Redbird understands both Databricks Delta table schemas and Commerce Cloud's OCAPI data structures, so you can connect customer behavior, product catalogs, and ML predictions without mapping APIs.
Redbird maps Commerce Cloud order objects, product catalogs, and customer profiles to Databricks Delta tables automatically. It understands nested attributes like basket line items, promotional adjustments, and custom site preferences—then structures them for analytics workloads. When you deploy predictions back to Commerce Cloud, Redbird handles customer list segmentation, product set assignments, and A/B test groups without custom transformation logic.
faster than building Spark jobs to parse Commerce Cloud APIs and sync predictions
Redbird can pull from Databricks and Salesforce Commerce Cloud simultaneously, merge the results, and format a polished report — sent on a schedule or on demand.
Set conditions in natural language. Get notified in Slack or email the moment a threshold is crossed in either Databricks or Salesforce Commerce Cloud.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Databricks into Salesforce Commerce Cloud, or from Salesforce Commerce Cloud back into Databricks. Resolve conflicts with configurable merge rules.
Every workflow run is logged — what ran, what changed, and why. Replay or revert any individual step at any time.
Start automations from new orders in Commerce Cloud or completed model runs in Databricks—Redbird handles the rest.
Trigger when new data is written to a specified Delta table or partition in Databricks.
Trigger when a registered MLflow model finishes training and is ready for deployment.
Trigger when a scheduled Databricks notebook job completes successfully with new results.
Append or merge prediction results into a specified Delta table with proper schema enforcement.
Execute a Databricks notebook with dynamic parameters like customer segment IDs or date ranges.
Refresh feature values in Databricks Feature Store for specified customer or product entities.
Trigger when a new order is completed in Commerce Cloud, capturing transaction and customer details.
Trigger when products are added, modified, or removed from the Commerce Cloud catalog.
Trigger when customer account data changes, including address updates or preference modifications.
Add or remove customers from segmentation lists used for personalized promotions and targeting.
Assign specific product IDs to recommendation slots for individual customers or segments.
Write custom attributes to customer profiles like predicted LTV or propensity scores from Databricks models.
Start syncing Commerce Cloud data to Databricks and deploying ML predictions back to your storefront—no pipeline engineering required.