Redbird AI automates the sync between your data orchestration layer and analytics platform. Stop manually checking pipeline statuses before refreshing dashboards, building custom scripts to expose DAG metadata to business users, or coordinating pipeline schedules with BI refresh timing.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically refresh specific Looker explores and dashboards the moment your Airflow pipeline finishes loading fresh data. Ensure stakeholders always see up-to-date analytics without manual intervention or fixed schedules that waste compute.
Surface Airflow task failures and data quality issues directly in Looker as contextual alerts on affected dashboards. Business users see why metrics are stale and estimated resolution times without leaving their analytics workspace.
Push pipeline run history, task durations, and data freshness timestamps from Airflow into Looker tables. Enable business users to self-serve data quality checks and understand exactly when their reports were last updated.
Monitor Looker for specific query patterns or timeout errors that suggest missing or incomplete upstream data. Trigger targeted Airflow DAG reruns to backfill gaps without full pipeline restarts.
Detect when critical ETL jobs miss their SLA windows and automatically delay Looker report delivery until fresh data arrives. Prevent executives from receiving dashboards with outdated or incomplete metrics.
Cross-reference which Looker dashboards are most frequently accessed with their upstream pipeline costs and runtime. Identify optimization opportunities by understanding which data transformations actually drive business value.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Airflow and Looker 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 Airflow's orchestration layer—DAGs, tasks, dependencies, and execution states—and Looker's semantic layer, including LookML models, explores, and dashboard refresh patterns.
Redbird automatically connects the dots between your Airflow task execution graph and the Looker explores that depend on that data. Our AI interprets DAG success callbacks, parses task logs for row counts and quality checks, then intelligently determines which Looker content needs refreshing. We understand the difference between a full pipeline rebuild versus an incremental update, and route the appropriate refresh commands to specific explores, dashboards, or embedded analytics endpoints without you mapping every dependency manually.
faster pipeline-to-BI orchestration than building custom Airflow operators
Redbird can pull from Airflow and Looker 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 Airflow or Looker.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from Airflow into Looker, or from Looker back into Airflow. 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 event in your orchestration layer or analytics platform, then execute actions across both systems.
Fires when a specific Airflow DAG finishes with success, failure, or any configured state.
Triggers when an individual task exhausts all retry attempts and enters a failed state.
Activates when custom sensor tasks detect row count anomalies or validation rule violations.
Programmatically start a specific DAG with optional runtime configuration parameters.
Reset failed or skipped tasks to enable partial pipeline reruns without full DAG restarts.
Modify Airflow variables or connection parameters dynamically based on external conditions.
Fires when a Looker scheduled report or alert fails to generate or send successfully.
Triggers when specific explores or dashboards consistently hit query time limits indicating performance issues.
Activates when changes to the semantic layer are pushed to production, potentially requiring pipeline adjustments.
Trigger rebuilds of specific persistent derived tables after upstream data updates complete.
Programmatically append data lineage details or last-updated timestamps to dashboard documentation.
Create targeted Looker alerts with pipeline context when data anomalies or SLA breaches occur.
Start automating between Airflow and Looker in minutes. Redbird handles the orchestration-to-analytics handoff so your data team can focus on building pipelines, not babysitting integrations.