Sync Heap's auto-captured interaction data directly into Databricks for advanced analysis, ML modeling, and cross-platform insights. Stop manually exporting CSVs or building custom pipelines to get product behavior into your lakehouse.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically sync all user interactions captured by Heap into Delta Lake tables in Databricks. Keep product behavior data fresh for real-time dashboards and streaming ML features without batch exports or manual refreshes.
Push churn risk, conversion likelihood, or LTV predictions from Databricks feature stores back into Heap as user properties. Enable product teams to segment and analyze users based on ML-driven insights without SQL knowledge.
Automatically merge Heap's granular clickstream with transactional, support, and CRM data from your lakehouse. Generate weekly reports showing how user behavior correlates with revenue, retention, and customer health metrics.
Run anomaly detection models on Heap funnel data stored in Databricks. Automatically notify product and growth teams when conversion rates, drop-off points, or user flows deviate from expected patterns.
Automatically move older Heap interaction data from active analytics systems into long-term Delta Lake storage. Maintain complete behavioral history for compliance and retroactive analysis while optimizing Heap retention costs.
Combine Heap's auto-captured web and mobile interactions with email, advertising, and offline data in Databricks. Build comprehensive user journey models that predict outcomes across your entire customer experience, not just digital touchpoints.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Databricks and Heap 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 Heap's event schemas and Databricks table structures, intelligently mapping user interactions, sessions, and properties to Delta Lake without custom engineering.
Redbird automatically recognizes Heap's event taxonomy—pageviews, clicks, form submissions, custom events—and maps them to optimized Delta tables with proper partitioning and schema evolution. It understands session stitching, user identity resolution, and how to preserve Heap's retroactive analysis capabilities while normalizing data for Spark processing. No manual schema mapping or JSON parsing required.
faster than building custom Heap export pipelines to Databricks
Redbird can pull from Databricks and Heap 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 Heap.
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 Heap, or from Heap 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 from any event in Heap or table change in Databricks—Redbird handles the orchestration across both platforms.
Fires when new data is written to a specified Delta Lake table in Databricks.
Triggers when a machine learning model finishes training and registers in MLflow.
Fires when a Databricks notebook completes execution on a defined schedule.
Insert or upsert rows into a specified Delta Lake table with merge logic.
Execute a registered ML model against new data for batch predictions.
Execute a Databricks notebook with dynamic parameters passed from workflow context.
Fires when Heap auto-captures a new user interaction matching specified criteria.
Triggers when a user qualifies for a behavioral segment based on interaction patterns.
Fires when a user successfully completes a defined multi-step funnel in Heap.
Attach custom properties to user profiles for segmentation and analysis.
Define a new user segment based on specific interaction patterns or event sequences.
Enrich captured events with additional context or classification tags.
Sync Databricks with Heap in minutes and start training models on complete behavioral data. Stop building and maintaining custom integration pipelines.