Connect Braze and
Databricks with AI

Redbird AI syncs campaign events, user profiles, and engagement data between Braze and Databricks — no more manual exports, CSV uploads, or brittle ETL scripts. Build closed-loop marketing workflows where ML models power segmentation and campaign results feed analytics pipelines automatically.

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.

Stream Braze campaign events and user behavior to Databricks for analysis

Automatically sync email opens, push sends, in-app interactions, and custom events from Braze to your Databricks lakehouse. Redbird handles schema evolution and deduplication, giving your data science team clean event streams for attribution modeling, customer journey analysis, and retention studies without manual exports.

Enrich Braze user profiles with ML-powered propensity scores from Databricks

Push churn risk scores, product affinity predictions, and lifetime value estimates from Databricks models directly into Braze as custom attributes. Marketing teams can segment audiences and personalize messaging using real-time ML features without waiting on engineering to build custom pipelines.

Sync Braze segment membership to Databricks for feature engineering

Keep Databricks feature stores updated with current Braze segment assignments, campaign membership, and engagement states. Data scientists can use marketing context as ML features while maintaining a single source of truth for customer attributes across the stack.

Build daily campaign performance dashboards from Braze metrics in Databricks

Automatically aggregate send volume, conversion rates, and engagement metrics from Braze into Databricks tables powering your BI layer. Redbird joins campaign data with purchase events, support tickets, and product usage to show true ROI without manual reporting work.

Update Braze audience segments with real-time cohort assignments from Databricks

Sync behavioral cohorts, lookalike audiences, and dynamically-scored user lists from Databricks streaming jobs into Braze segments. Campaigns stay targeted to the latest ML-identified audiences without batch delays or manual list uploads.

Archive Braze message content and A/B test results to Databricks

Preserve campaign creative, variant configurations, and test outcomes in your Databricks lakehouse for compliance and historical analysis. Build institutional knowledge of what messaging works across channels, products, and customer segments with queryable archives of every campaign.

Live in four steps

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

01

Connect your accounts

Authorize Braze and Databricks 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 understands Braze's campaign structure, custom event schemas, and user attribute model alongside Databricks table formats, Delta Lake versioning, and streaming job patterns.

AI that maps campaigns to lakehouses automatically

Redbird's AI interprets Braze's nested event payloads, Canvas step metadata, and custom attribute types, then maps them to optimized Delta tables in Databricks. It handles incrementality across Currents exports, resolves user ID conflicts between external_id and aliases, and maintains schema history as your Braze data model evolves. When syncing features back to Braze, Redbird validates data types against subscription group rules and custom attribute limits automatically.

Currents event streaming
Delta Lake schema evolution
Custom attribute mapping
User ID resolution
10×

Faster than building custom Currents + Databricks ETL pipelines

No Spark job development, S3 bucket management, or schema migration scripts required

Auto-generated reports

Redbird can pull from Braze and Databricks 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 Braze or Databricks.

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 Braze into Databricks, or from Databricks back into Braze. 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 campaign sends in Braze or completed ML jobs in Databricks — Redbird connects every event across both platforms.

Braze
Triggers & Actions
Trigger

Campaign sent

Fires when a Braze campaign or Canvas message is sent to users.

Trigger

User profile updated

Triggers when custom attributes, subscription states, or user tags change in Braze.

Trigger

Custom event received

Activates when Braze receives a specific custom event like purchase, content_view, or app_opened.

Action

Update user attributes

Write or update custom attributes, tags, or email subscription status for Braze user profiles.

Action

Add users to segment

Assign user profiles to specific Braze segments or remove them based on upstream conditions.

Action

Track custom event

Send custom events back to Braze to trigger Canvas flows or update user engagement history.

Databricks
Triggers & Actions
Trigger

Notebook job completes

Fires when a scheduled Databricks notebook finishes running, whether for ETL, training, or scoring.

Trigger

Delta table updated

Triggers when new data is written to a specified Delta Lake table or partition.

Trigger

ML model registered

Activates when a new model version is logged to MLflow model registry in Databricks.

Action

Run notebook job

Execute a Databricks notebook with parameters, triggering feature generation or model scoring workflows.

Action

Write to Delta table

Append or merge records into Delta Lake tables, maintaining schema and handling duplicates automatically.

Action

Query SQL warehouse

Run SQL queries against Databricks SQL endpoints and use results in downstream automation steps.

Braze
+
Databricks

Ready to connect your stack?

Stop building custom pipelines between Braze and Databricks. Redbird handles the complexity so your team can focus on better campaigns and deeper insights.

Get started → Book a demo