Connect Amazon Seller Central and
Databricks with AI

Redbird AI automates the flow of seller performance, inventory, and order data from Amazon Seller Central into Databricks. Stop exporting CSVs, writing brittle scripts, or waiting on engineering to refresh your lakehouse tables. Keep your ML models and analytics pipelines current with real-time marketplace data.

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 Amazon sales and order data into Delta Lake tables

Automatically ingest settlement reports, order details, and fulfillment status from Seller Central into Databricks Delta tables. Redbird handles incremental updates, deduplication, and schema evolution so your lakehouse always reflects current marketplace activity without manual file uploads.

Build real-time inventory forecasting models from marketplace data

Flow inventory levels, sell-through rates, and restock recommendations from Amazon into feature tables in Databricks. Train ML models on historical sales velocity and seasonality, then automate retraining as new marketplace data arrives to improve forecast accuracy.

Centralize advertising and organic sales metrics for unified attribution

Combine Sponsored Products spend, impressions, and conversions with organic order data in Databricks. Run cross-channel attribution models and ROAS analysis across your entire Amazon presence without stitching together multiple report downloads.

Sync ML-generated pricing recommendations back to product listings

Push dynamic pricing outputs from Databricks models directly to Amazon Seller Central SKUs. Automate competitive price adjustments based on demand forecasts, inventory position, and profitability thresholds calculated in your lakehouse without manual repricing workflows.

Archive seller performance and account health data for compliance

Automatically capture account health ratings, customer feedback, A-to-Z claims, and policy notifications into versioned Delta tables. Maintain audit trails and historical snapshots for compliance reviews, chargebacks analysis, and long-term seller performance benchmarking.

Alert operations when anomaly detection identifies fulfillment issues

Run anomaly detection models in Databricks on order defect rates, late shipment metrics, and return volumes. Trigger alerts and push flagged ASINs or seller accounts back to Amazon dashboards when models detect statistically significant performance degradation requiring immediate action.

Live in four steps

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

01

Connect your accounts

Authorize Amazon Seller Central 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 AI understands both Amazon Seller Central's marketplace data structures and Databricks' lakehouse architecture, automatically mapping seller reports to optimized Delta table schemas.

AI that reads settlement reports, order schemas, and Spark table definitions

Redbird's AI automatically interprets Amazon's settlement reports, inventory feeds, advertising data, and order line items — then maps them to Databricks Delta tables with proper partitioning and optimization. It handles Amazon's nested product attributes, variant hierarchies, and fulfillment channel complexity, generating appropriate schemas and merge logic for slowly changing dimensions. When Amazon updates report formats or you refactor your lakehouse structure, Redbird adapts without breaking pipelines.

Delta Lake upserts for order updates
Partition by marketplace and date
Parse nested ASIN attributes
Handle FBA vs. FBM data structures
10×

faster seller data pipelines vs custom Spark scripts

No manual schema mapping, file parsing logic, or API pagination code required

Auto-generated reports

Redbird can pull from Amazon Seller Central 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 Amazon Seller Central 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 Amazon Seller Central into Databricks, or from Databricks back into Amazon Seller Central. 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 seller event in Amazon or table update in Databricks — no code required.

Amazon Seller Central
Triggers & Actions
Trigger

New settlement report available

Trigger when Amazon generates a new settlement period report with transaction-level financial data.

Trigger

Inventory level drops below threshold

Fire when available inventory for an ASIN falls below your restock point across fulfillment centers.

Trigger

Account health metric changes

Trigger on updates to order defect rate, late shipment rate, or policy violation status.

Action

Update product listing price

Modify the sale price for a SKU or ASIN in your Seller Central catalog.

Action

Adjust inventory quantity

Update available inventory levels for FBM listings or create removal orders for FBA stock.

Action

Create or update product listing

Add new ASINs to your catalog or modify titles, descriptions, images, and attributes for existing listings.

Databricks
Triggers & Actions
Trigger

Delta table updated with new rows

Fire when new data is appended to a specified Delta Lake table in your lakehouse.

Trigger

ML model training completes

Trigger when a scheduled MLflow model training run finishes and registers a new model version.

Trigger

Notebook execution finishes

Fire when a Databricks job or notebook completes, whether successful or failed.

Action

Write records to Delta table

Insert, update, or merge data into a Delta Lake table with automatic schema handling.

Action

Execute SQL query or notebook

Run a parameterized SQL statement or trigger a Databricks notebook with custom variables.

Action

Update feature store values

Refresh feature values in a Databricks Feature Store table for real-time model inference.

Amazon Seller Central
+
Databricks

Ready to connect your stack?

Stop building custom ETL for Amazon seller data. Redbird AI connects Amazon Seller Central and Databricks in minutes, keeping your lakehouse synchronized with marketplace performance without engineering overhead.

Get started → Book a demo