I’m moving into Phase 2 of a document-processing platform and need the backend extended so it reliably pulls data out of incoming files and automatically routes that information through our internal workflows. The core of this phase is twofold: first, refine and expand the data-extraction pipeline so the service can ingest new document feeds, parse key fields, and expose them through clean, versioned APIs; second, build the rules-driven workflow engine that takes those parsed results and triggers downstream actions without manual intervention. My existing codebase is modular and well-commented; you’ll be able to slot your work in with minimal friction, whether you prefer Python, Node.js, or Java. The important part is clean architecture, high test coverage, and clear documentation so the system remains maintainable as we add further automation features. Deliverables that will mark this phase complete: • Source code pushed to the shared Git repository, following the current style guide • API endpoints for document ingestion, extraction results, and workflow status • Configuration-based workflow module that supports new rules without redeploying code • Unit and integration tests covering at least 85 % of new functionality • A concise technical README that explains setup, deployment, and extension points Acceptance criteria include accurate extraction of designated fields, consistent processing times under expected load, and automated workflow completion confirmed in the test suite. If you’ve built similar ETL or process-automation backends, especially around unstructured documents, your experience will fit perfectly. Let’s discuss architecture details and get Phase 2 shipped.