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CashMed

CashMed
Project overview ↘

Fintech solution specialized in credit anticipation and cash flow management for doctors and clinics. Developed with a Django backend for secure financial operations (ACID), a React frontend, an integrated KYC pipeline with AI for fraud prevention, and over R$ 10M in managed transactions.

Fintech for receivables anticipation and financial infrastructure for the healthcare sector.

StatusCompleted
Created atMay 2026
Views3
Technologies05
Technologies
No-Code (Bubble)DjangoReactPostgreSQLRedis
Tags
FintechInteligência ArtificialAutomaçãoDesenvolvimento Ágil
Section / 01Project dossier

Challenge, decisions and result

CashMed is a fintech that operates as a structured financial operating system for the healthcare ecosystem. The platform centralizes the payment flow for clinics and hospitals, processes the split of medical fees, and offers an integrated solution for immediate liquidity through an automated receivables anticipation engine.

Product Engineering: From POC to Fintech Infrastructure

To validate the credit model and user behavior with the shortest possible Time-to-Market, we validated the Proof of Concept (POC) using No-Code (Bubble).

Once the product's viability and demand for liquidity were confirmed, I led the migration and complete reengineering to a robust and highly secure architecture, essential for financial systems:

  • Backend (Django): Architecture designed to ensure compliance with ACID properties, strict concurrency control, transaction auditing in the ledger, and asynchronous queues for payment processing.
  • Frontend (React): High-performance financial dashboards with real-time updates on balances, receivables projections, and credit applications in just a few clicks.

Technological and Fintech Pillars

  • Credit Anticipation Engine: Proprietary algorithm that analyzes the predictability of clinic disbursements based on operational history, generating automatic anticipation offers with dynamic fee calculations.
  • Automated KYC & Compliance with AI: An artificial intelligence (Vision/LLM) pipeline integrated into onboarding for automated validation of professional documents (CRM, diplomas, and banking data), reducing the risk of identity theft.
  • Fee Splitting and Reconciliation: A banking reconciliation engine that automates the flow of disbursements and generates complex financial reports, such as the Income Statement (DRE) in real-time for partner clinics.
  • Shift Management as a Data Lever: The shift functionality acts as the main feeder for the financial engine, mapping future receivables of doctors and serving as collateral for credit release.

Volume and Scale Metrics (In Production)

  • R$ 10M+ in Managed Medical Fees.
  • 500+ Active Medical Users generating credit history.
  • 50+ Clinics and Hospitals operating as paying hubs.
  • 98% Satisfaction in the liquidity anticipation experience.
End of case study / 06

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