Programmed a brutally strict PHI de-identification pipeline allowing private medical datasets to enter public research without stripping critical clinical context.
Clinical research requires PHI de-identification. Manual redaction is slow and error-prone. Most automated tools miss contextual identifiers or over-redact, destroying data utility.
De-id.org uses NLP to intelligently strip identifiers while preserving medical meaning. Built for researchers who need compliant datasets, fast.
Domain expertise in Healthcare. Systems built for scale without overengineering. Pragmatic tech choices that ship.
Detailed technical schematics and documentation for De-id.org are proprietary and available upon request for deep-dive discussions.
Technical constraints forced creative solutions. We optimized for Healthcare from day one, which meant rethinking architecture at every layer. Shipped incrementally, validated with real users, and scaled what worked.
Delivered on scope, timeline, and technical requirements
SaaS margin lives in simplicity. Cut scope aggressively, automate everything, and let pricing scale with value delivered.
A methodology for moving AI from experiments to operating systems. Four phases, built on lessons from digital and cloud transformation waves, tested across healthcare, consumer tech, and agencies.