Case Study · Jeffrey James Idodo
BFLOW RCM Platform
AI-powered revenue-cycle automation for healthcare operations.
AI/LLMSupabasePostgreSQLRLSEdge FunctionsEDI
Problem
Healthcare revenue-cycle workflows were manual, fragmented, and error-prone across claims, payments, and denials.
Constraints
HIPAA-aware data handling; multi-tenant isolation; auditability; integration with existing EDI transaction formats.
Architecture
AI-assisted automation on a multi-tenant Supabase backend (RLS isolation), server-authoritative Edge Functions, and event-driven EDI pipelines.
Solution
Automated the revenue cycle end-to-end — claims → eligibility → payments → denials → reporting — with AI-assisted workflows over connected, auditable data.
Outcome
Less manual touch and rework; faster claim-to-cash; improved data integrity and operational scale across tenants.