Building AI-Powered Revenue Cycle Management Systems
Senior Software Engineer at BFLOW Solutions — modernizing healthcare operations through AI-assisted automation, EDI infrastructure, and scalable multi-tenant platforms.
Current Impact
At BFLOW Solutions, I build the AI-powered systems that run healthcare revenue-cycle operations — automating claims, modernizing legacy platforms, and scaling a multi-tenant architecture dozens of practices depend on.
AI-powered RCM automation
Claims, eligibility, denials, and reconciliation driven by AI-assisted workflows.
EDI transaction infrastructure
Core healthcare transaction sets ingested and turned into operational flows.
Legacy platform modernization
Consolidating fragmented healthcare systems into one modern platform.
Multi-tenant architecture
RLS-isolated tenancy so 50+ practices share infrastructure, never data.
Built for scale, data integrity, and audit from day one.
Architecture Highlights
AI-Powered Revenue Cycle Platform
- Problem
- Revenue-cycle work is manual, slow, and error-prone — claims, denials, and reconciliation eat staff hours.
- Architecture
- AI-assisted automation over a Supabase backend; event-driven pipelines; server-authoritative Edge Functions.
- Business Impact
- Less manual touch, faster claim-to-cash, fewer denials slipping through.
Healthcare Claims Automation
- Problem
- Claims arrive as opaque EDI files with no automated path into operations.
- Architecture
- AI-assisted parsing + normalization of 837/835/277/999 into structured, auditable workflows.
- Business Impact
- Claims processed faster and more accurately, with a full audit trail.
EDI Processing Infrastructure
- Problem
- Healthcare transactions must be exchanged reliably and compliantly across payers.
- Architecture
- Ingestion → normalization → reconciliation pipelines on serverless Edge Functions; secrets off-client.
- Business Impact
- Reliable, compliant transaction exchange operations can trust.
Multi-Tenant Healthcare Architecture
- Problem
- Dozens of isolated systems duplicate effort and fragment data.
- Architecture
- One platform, Supabase RLS tenant isolation, tracked migrations, least-privilege access.
- Business Impact
- 50+ practices on shared infrastructure with provable data isolation — scales without re-architecting.
Helping modernize healthcare revenue-cycle operations — through AI-assisted automation, EDI infrastructure, and multi-tenant platform architecture.
Featured Work
BFLOW RCM Platform
AI-powered revenue-cycle automation for healthcare operations.
- 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.
Multi-Tenant Database Migration
Consolidating isolated healthcare systems into one platform.
- Problem
- Dozens of isolated healthcare databases meant duplicated effort, inconsistent data, and no unified operational view.
- Constraints
- Zero data loss; tenant isolation; HIPAA-aware access control; migrate without disrupting live operations.
- Architecture
- Unified multi-tenant schema with Supabase Row-Level Security per tenant; tracked migrations; least-privilege access; data-integrity validation.
- Solution
- Migrating 50+ healthcare databases into a single RLS-isolated multi-tenant platform.
Outcome — Unified architecture, consistent data integrity, and a foundation that scales with new tenants.
EDI Automation Platform
Turning healthcare transactions into operational workflows.
- Problem
- Healthcare EDI transactions (837/835/277/999) arrived as opaque files with no automated path into operations.
- Constraints
- Format fidelity; auditability; reliability; compliant handling of sensitive data.
- Architecture
- Ingestion → normalization → reconciliation pipelines on serverless Edge Functions, with audit trails and secure storage.
- Solution
- Automated claims-processing pipelines that parse and route 837/835/277/999 into normalized operational workflows.
Outcome — Faster, auditable claims processing replacing manual transaction handling.
JeffOS
An operating-system-style portfolio, built from scratch.
- Problem
- How do you prove engineering range, not just claim it?
- Constraints
- Real backend, real realtime, real performance/accessibility budgets — not a demo.
- Architecture
- React 19 windowing OS, capability-based responsive shells, Supabase realtime via a counter pattern, PWA, tracked migrations, security-hardened RLS.
- Solution
- A working web OS with apps, realtime visitor counts, themes, and a security/scalability-audited backend.
Outcome — Proof of systems thinking — the portfolio is itself the engineering demo.
Why Hire Jeffrey
He builds AI-powered RCM, end to end
Claims, denials, eligibility, reconciliation — automated, not just digitized.
He speaks healthcare and infrastructure
EDI, RCM, HIPAA constraints, multi-tenant scale — no translation layer between domain and code.
He modernizes without breaking operations
Legacy consolidation and migrations that ship audit-ready: RLS, tracked migrations, observability.
If your healthcare platform needs AI-driven automation that scales and survives an audit — that's the work I do.
Experience
Senior Software Engineer
CurrentBFLOW Solutions · Remote · Dec 2025 – Present
- Building AI-powered revenue-cycle automation — claims, denials, eligibility, reconciliation.
- EDI transaction infrastructure — 837/835/277/999 into operational workflows.
- Leading a multi-tenant migration of 50+ healthcare databases onto Supabase with RLS isolation.
- HIPAA-aware secure data layers (RLS + RBAC) and serverless Edge processing.
Project & Technology Officer
Eastley Park Limited · May 2025 – Sep 2025
- Designed automation + multi-system data workflows via API integrations.
- Owned backend process design and documentation for team scalability.
Project Manager / Automation Engineer
Fobat Properties · Jun 2022 – Aug 2024
- Led database-driven reporting systems; improved accuracy and auditability.
- Owned backend-dependent projects from requirements through delivery.
Network Operations Engineer
Suburban Fibreco · May 2016 – Oct 2017
- Maintained 99% SLA uptime for enterprise clients — reliability-engineering discipline.
- Diagnosed and resolved 200+ network/system issues.
Education
- B.Sc. Computer Science — Redeemer's University2015 – 2019
- Full-Stack Web Development — New Horizons Nigeria2025
Available For
This entire site is a macOS Tiger recreation I built from scratch.
A faithful Mac OS X Tiger desktop — windowing, Spotlight, Exposé, Dashboard, a glass dock, realtime, a security-audited Supabase backend, tracked migrations, PWA — with an iPhone-OS-style home screen on mobile. The same rigor I bring to healthcare systems, turned on my own portfolio: systems thinking, frontend architecture, performance engineering, and platform design.
Contact
Let's talk about systems worth building.