Sync development activity from GitHub directly into Snowflake for analysis. Stop writing custom ETL scripts, manually exporting commit data, or running fragile API sync jobs to get engineering metrics into your warehouse.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically capture every commit, PR merge, code review, and branch activity from GitHub into structured Snowflake tables. Build dashboards on developer velocity, cycle time, and deployment frequency without maintaining custom scripts.
Sync workflow execution data, build times, test results, and deployment events into Snowflake. Analyze pipeline performance, failure patterns, and resource usage across all repositories and teams.
Store complete issue lifecycle data—creation, assignments, labels, milestones, and closures—in Snowflake. Maintain a permanent record of engineering work for trend analysis and capacity planning.
Trigger issue creation in GitHub when Snowflake queries detect data pipeline failures, schema drift, or quality threshold violations. Route alerts directly to the engineering teams responsible for data infrastructure.
Use contributor analysis stored in Snowflake to intelligently assign pull request reviewers. Match code changes with developers who have domain expertise based on historical commit patterns and file ownership.
Correlate GitHub releases and deployments with business KPIs stored in Snowflake. Tag commits and PRs with downstream impact on revenue, usage, or performance metrics for context-aware development.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize GitHub and Snowflake 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 GitHub's event-driven structure and Snowflake's columnar schemas, so you can automate data flows between development activity and analytics without writing transformation logic.
Redbird automatically maps GitHub's nested JSON payloads—commits, pull requests, Actions runs, issue events—into clean, queryable Snowflake tables. The AI handles schema evolution when GitHub adds fields, manages incremental sync strategies, and creates appropriate indexes for time-series queries on development activity. No need to maintain dbt models or Airflow DAGs just to get engineering data into your warehouse.
faster than building custom GitHub API → Snowflake ETL pipelines
Redbird can pull from GitHub and Snowflake 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 GitHub or Snowflake.
SOC 2 Type II certified. Data flows encrypted in transit and at rest. Fine-grained permission controls with full audit logs.
Push data from GitHub into Snowflake, or from Snowflake back into GitHub. 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 GitHub event or Snowflake query result—Redbird handles the rest.
Trigger when a PR is created, updated, approved, or merged in any repository.
Fire when new commits are pushed to specific branches or across all repositories.
Detect when CI/CD pipelines finish, including status, duration, and artifacts.
Open new issues or modify existing ones with labels, assignees, and milestones.
Post automated comments on PRs with analysis results or approval requirements.
Programmatically start workflow runs with custom inputs and parameters.
Fire when a scheduled Snowflake query returns results matching specific conditions.
Detect when data lands in specific Snowflake tables or views via streams.
Trigger when validation queries identify anomalies, nulls, or schema issues.
Write new data or upsert existing records with conflict resolution logic.
Run queries with dynamic inputs from GitHub data to update or analyze records.
Programmatically configure data pipelines and change tracking objects.
Start syncing GitHub development activity with Snowflake analytics in minutes. Stop maintaining custom ETL scripts and get engineering metrics into your warehouse automatically.