Redbird AI automates the flow between your event streams and analytics warehouse. Stop writing custom consumers, manual ETL scripts, and one-off jobs to sync Kafka topics with BigQuery tables or push analytical results back to real-time pipelines.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically consume messages from Kafka topics and write them to BigQuery tables with proper schema mapping and partitioning. Redbird handles deserialization, type conversion, and incremental loads without custom consumer code.
Run scheduled queries in BigQuery and publish results as events to Kafka topics. Power downstream applications with enriched data, ML predictions, or aggregated metrics from your warehouse without building custom producers.
Intercept Kafka messages, query BigQuery for reference data or customer attributes, and republish enriched events to a new topic. Redbird manages the join logic, caching, and throughput optimization automatically.
Automatically sink entire Kafka topics to BigQuery with compression, partitioning by event timestamp, and deduplication. Preserve raw event data for compliance, historical analysis, and model training without managing connector infrastructure.
Monitor BigQuery tables or scheduled query results and publish alert events to Kafka when anomalies, SLA breaches, or business thresholds are detected. Enable real-time response to warehouse insights across your event-driven architecture.
Export batch predictions from BigQuery ML models and stream them to Kafka topics for consumption by operational systems. Bridge the gap between warehouse-based model training and production inference without custom pipelines.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize BigQuery and Kafka 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 your BigQuery table schemas and Kafka topic structures, automatically handling serialization formats, partitioning strategies, and throughput requirements for bidirectional sync.
Redbird automatically maps between Kafka message schemas (Avro, JSON, Protobuf) and BigQuery table definitions, handling nested fields, repeated records, and type conversions. The AI understands partitioning strategies in both systems, optimizes batch sizes for BigQuery streaming inserts, and manages offset commits for exactly-once Kafka consumption. No need to write schema registries, serializers, or custom connector configs.
faster than building custom Kafka Connect configurations with BigQuery sink connectors
Redbird can pull from BigQuery and Kafka 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 BigQuery or Kafka.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from BigQuery into Kafka, or from Kafka back into BigQuery. 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 any BigQuery query result or Kafka topic event, then take action across your entire data stack.
Trigger when a scheduled or on-demand BigQuery query returns results matching specific conditions or thresholds.
Detect when new data is inserted into a BigQuery table based on timestamp or incremental key columns.
Trigger when BigQuery ML batch prediction jobs finish and write results to a destination table.
Execute a BigQuery SQL query with dynamic parameters from upstream data or Kafka events.
Write records to BigQuery tables with automatic schema validation and streaming insert optimization.
Overwrite or append data to specific BigQuery table partitions based on date or other partition keys.
Consume messages from Kafka topics with automatic deserialization and offset management.
Trigger when Kafka consumer group lag crosses a specified threshold for monitoring and alerting.
Detect when Kafka topic partitions are reassigned or rebalanced across the cluster.
Produce messages to Kafka topics with automatic serialization, partitioning, and delivery confirmation.
Provision new Kafka topics or modify existing topic configurations including partition count and retention.
Manually commit Kafka consumer offsets after successful downstream processing to ensure exactly-once semantics.
Stop building and maintaining custom Kafka consumers and BigQuery ETL pipelines. Redbird AI connects your event streams and analytics warehouse with intelligent automation that adapts to your schemas and scales with your data volume.