Client: Ritten (Healthcare Data Management Company)

Technology Stack: Google Cloud Run, Vertex AI, Transcription API, Cloud Storage, AlloyDB, Cloud Functions, Gemini, Google Cloud VPC, Sensitive Data Protection API, Terraform

I led a GenAI Pilot project for Ritten, focusing on enhancing their data management capabilities using Google Cloud Platform (GCP). This project had two main goals:

Voice-to-Text Transcription and Text Extraction:

Functionality: Developed a solution to transcribe voice recordings to text using the Transcription API, and extract predefined field values from the text transcripts using Vertex AI. The transcripts were then fed to Gemini for summarization and form-filling. These extracted values were formatted in JSON, enabling automated form filling.

Benefits: The solution simplified the process for clinicians and administrators, allowing them to efficiently manage patient data while meeting HIPAA guidelines. This automated system significantly reduced manual data entry efforts, saving nurses hours of time and improving accuracy.

Scalable and Extensible Architecture:

Functionality: Designed a secure, multi-tenant cloud environment using Terraform for provisioning resources. Implemented data scrubbing and anonymization to ensure privacy and compliance with HIPAA regulations.

Benefits: The scalable architecture supports future growth and integration with existing systems, providing a strong foundation for ongoing improvements and additional features.

Impact: This project successfully showed the potential of GCP to enhance Ritten's platform by automating complex data management tasks. By integrating advanced AI and cloud technologies, we delivered a solution that not only improves operational efficiency but also ensures compliance and scalability for future needs.