Redbird AI automates the flow of engineering data from Jira into Redshift, eliminating manual exports and custom ETL scripts. Stop building one-off pipelines to track sprint metrics, issue lifecycles, and delivery performance—let AI sync your project data directly to your warehouse for consistent, queryable insights.
Redbird gives your team ready-to-run workflows — just connect your accounts and go.
Automatically sync every issue creation, status change, and field update from Jira into Redshift tables. Build a complete historical record of your engineering work for trend analysis, cycle time calculations, and velocity reporting without manual exports or delayed batch jobs.
When a sprint closes in Jira, capture all issue data, story points, completion status, and timestamps into a Redshift fact table. Create a queryable archive of sprint performance that powers executive dashboards and helps identify patterns in delivery predictability.
Pull revenue, usage, or customer tier data from Redshift and write it back to custom fields in Jira issues. Empower engineering teams to prioritize bugs and features based on actual customer impact metrics stored in your warehouse.
Run scheduled queries in Redshift to detect spikes in bug creation rates, declining velocity, or accumulating tech debt. Automatically create Jira issues or update dashboards when warehouse analytics identify concerning trends in your engineering metrics.
Automatically pipeline Jira issue lifecycle events, comments, and assignment changes into Redshift every day. Join this data with deployment logs and customer data to build comprehensive engineering health reports without wrestling with the Jira API or CSV exports.
Capture Jira version releases, fix versions, and deployment flags directly into Redshift dimension tables. Connect release metadata with production metrics, incidents, and customer behavior data for complete release impact analysis.
No engineers, no pipelines to maintain. Redbird handles the connectivity — you focus on the outcome.
Authorize Jira 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 understands Jira's project schemas, custom fields, and agile workflows alongside Redshift's columnar storage, distribution keys, and query patterns—no manual schema mapping required.
Redbird automatically maps Jira's issue types, custom fields, sprint data, and workflow statuses to optimized Redshift table structures. The AI handles schema evolution when you add custom fields in Jira, manages data type conversions between systems, and structures warehouse tables with appropriate sort keys and distribution strategies for fast analytical queries. It understands the difference between slowly-changing dimensions like user assignments and fast-moving fact tables like issue status transitions.
faster than building custom Jira-to-Redshift ETL pipelines
Redbird can pull from Jira 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 Jira 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 Jira into Redshift, or from Redshift back into Jira. 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 issue event in Jira or query result in Redshift—Redbird handles the rest.
Trigger when a new issue is created in any project or matching specific issue types.
Trigger when an issue moves between workflow states like To Do, In Progress, or Done.
Trigger when a sprint closes, capturing all final issue states and velocity metrics.
Create new Jira issues with custom fields populated from warehouse data.
Write data back to standard or custom Jira fields based on analytics or external triggers.
Post automated comments to issues with insights or alerts from warehouse queries.
Trigger when a scheduled Redshift query identifies rows matching specific analytical conditions.
Trigger when a table exceeds or falls below a defined row count, signaling data volume changes.
Trigger when fresh data arrives in specified Redshift tables via INSERT or COPY operations.
Run parameterized SQL queries in Redshift using data from Jira or other connected tools.
Write issue data, sprint metrics, or enriched attributes directly into Redshift tables.
Update existing Redshift records when Jira issue fields change or statuses are modified.
Sync Jira project data to Redshift in minutes and start building engineering analytics without writing ETL code. Redbird handles schema mapping, incremental updates, and data transformations automatically.