Teams often end up rebuilding the same runtime code—connection handling, retries, logging—in hundreds of standalone Python scripts. SeaTunnel fixes this by moving those concerns into a shared runtime and connector framework, leaving developers to define just the source, transform, and sink for each data pipeline.

Pluto Health aggregates patient data across EMRs, insurance, labs and social determinants of health from 90% of US systems, then applies AI to identify care gaps and risk factors. It integrates with existing workflows via API, white-label or clinical operations, delivering preventive services, screenings, at-home labs and trial pre-screening directly to patients. Continuous event monitoring tracks new diagnoses and insurance changes to ensure follow-up and close the care loop.

After juggling three insurance changes, the author built AI-driven workflows to automate health admin tasks—from finding missing reimbursements to consolidating lab results and family history—so she arrives at doctor visits with full context. These “conductor” experiments use tools like Claude and Flexpa to surface data gaps, flag trends, and suggest actions, letting patient and clinician collaborate more effectively.