Redbird AI automates cross-cloud data pipelines between GCP and AWS. Stop writing custom ETL scripts, managing file transfer jobs, or manually syncing object storage with your data warehouse. Build intelligent workflows that move and transform data across cloud boundaries.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically detect new files or partitions in Google Cloud Storage buckets and load them into Redshift staging tables with schema mapping. Redbird handles format conversion, compression, and incremental loads without manual COPY commands or AWS Data Pipeline configuration.
Move aged-out transactions, events, or analytical snapshots from Redshift to Google Cloud Storage buckets based on retention policies. Redbird automatically unloads tables, compresses data, and organizes files in GCS with lifecycle policies applied.
When BigQuery exports land in Cloud Storage, automatically ingest them into Redshift with schema reconciliation. Redbird maps GCP data types to Redshift equivalents and handles nested JSON flattening for compatibility with AWS analytics tools.
Export Redshift query results and materialized views to Google Cloud Storage in formats optimized for Vertex AI or Dataflow. Redbird schedules extracts, handles partitioning, and stages data for consumption by GCP ML workflows.
Before moving raw event files from Cloud Storage to Redshift, join them with dimension data already in your warehouse. Redbird queries Redshift for lookup values, enriches GCS objects in-flight, and loads complete denormalized records.
After loading GCS files into Redshift, automatically run validation queries and surface anomalies. Redbird compares row counts, checks for nulls in critical columns, and flags schema drift between source and warehouse.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Google Cloud Storage and Redshift 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 AI understands both Google Cloud Storage object structures and Redshift table schemas, so you can move data across GCP and AWS without writing cross-cloud integration code.
Redbird reads bucket hierarchies, file formats, and partition patterns in Google Cloud Storage, then maps them to Redshift dist keys, sort keys, and columnar compression. It handles Parquet, Avro, CSV, and JSON from GCS, automatically translating GCP data types to Redshift-compatible schemas. Redbird generates optimized COPY and UNLOAD statements, manages manifest files, and reconciles schema evolution between cloud providers without manual transformation logic.
faster than building custom cross-cloud ETL with Lambda, Glue, or manual COPY scripts
Redbird can pull from Google Cloud Storage and Redshift 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 Google Cloud Storage or Redshift.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Google Cloud Storage into Redshift, or from Redshift back into Google Cloud Storage. 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 workflows from any file event in Google Cloud Storage or table change in Redshift, then automate cross-cloud data movement and transformation.
Trigger when objects are uploaded to specified GCS buckets or prefixes.
Detect files matching naming conventions, formats, or partition structures.
Trigger when cumulative object storage crosses size or count limits.
Extract data from CSV, JSON, Parquet, or Avro files for transformation.
Upload processed files to GCS with compression and partitioning applied.
Move files to Nearline/Coldline storage classes or remove them based on policy.
Detect inserts, updates, or deletes in Redshift tables or schemas.
Trigger when aggregate queries return values outside expected ranges.
Respond when COPY commands finish loading external data into Redshift.
Execute COPY commands to ingest files from cloud storage into tables.
Export Redshift table data or query output to GCS or S3 buckets.
Execute CREATE TABLE AS, materialized views, or data cleaning queries.
Redbird AI eliminates the complexity of cross-cloud data integration. Connect Google Cloud Storage and Redshift in minutes and start automating pipelines that used to require dedicated data engineering.