Agentic Design, Development, and Deployment
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Automate end-to-end data engineering process for building pipelines including Databricks’ Medallion Architecture Bronze (raw data), Silver (cleansed data) and Gold (business-level aggregates) levels.
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From English language requirements (in Jira) to production-ready code (Python, PySpark, SQL, Notebook).
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Enterprise context from code repositories (Github) and catalogs.
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Built-in automated quality testing.
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Breakpoints for human developers to review and make changes.
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Enterprise-grade data privacy protections.
Purgo AI Playground: Build your own Data Pipelines
Try the product in a sandbox environment integrated with trial instances of Jira, GitHub and Databricks.
Explore Purgo AI’s powerful capabilities starting with the Purgo AI Jira App and pre-built Jira tickets capturing business requirements. Purgo AI Agents automate the development workflow:
1. Requirements
Specify requirements as user stories in Jira.
2. Design
​Generate design pseudo code (Gherkin) from requirements and enterprise context of GitHub and catalogs.
3. Test Data/Test Code
Generate datasets and test scripts from design prompt.
4. Develop Code
Generate code from design prompt and re-generate after applying tests.
5. Push to Production
Push to GitHub and Databricks.
