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Sole architect and lead engineer. Designed the full system: a custom PDF extraction pipeline parsing rate tables and benefit classifications, an AI ranking model scoring plans side-by-side, and an RFQ comparison engine. Made all infrastructure decisions — executed a full production migration from AWS EC2 to a Mailcow VPS under a live client deadline, resolving PostgreSQL and MongoDB compatibility issues in production.
The network for creativity
Join 1.25M professional creatives like you
Connect with clients, get discovered, and run your business 100% commission-free
Creatives on Contra have earned over $150M and we are just getting started
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A beautiful UI is just a statue. An integrated backend is a living entity."
I have officially completed the Frontend Architecture (The Body) for Synapse and successfully established the primary Data Bridge.
The Current Status:
The 16-column grid and kinetic UI components are now successfully pushing real-time data to the backend. This "handshake" marks the transition from a design artifact to a functional system.
What’s Next (The Momentum):
We are now moving into the Autonomous Nervous System phase. I am currently architecting the orchestration layer in n8n that will take these basic data inputs and transform them into intelligent outcomes, automating lead enrichment, complexity scoring, and CRM protocols.
The Goal: > A zero-latency environment where the website doesn't just display information, it processes it.
Building for speed. Engineering for scale.
aiwebdevelopmentaiautomationwebsiteaiautomatiomAI AutomationBusiness Workflow AutomationAI Engineer LovableN8NSupabase
Sendora is a global fintech platform that enables fast, secure cross-border money transfers with zero fees while also helping users build and manage their credit.
It combines international payments, multi-currency support, and credit tools into a single seamless digital experience for individuals and businesses.
Looks amazing
Medicine Supply Chain Disruption Predictor
Built a production-ready ML system that predicts drug shortage risk using real FDA data. Collected and cleaned 1703 real drug shortage records, trained an XGBoost model, and deployed it as a live REST API — accessible to anyone worldwide.
The biggest challenge was identifying and removing 6 sources of data leakage that were causing fake 100% accuracy. After fixing this, the model delivers honest, generalisable predictions.
The entire system is containerised with Docker, automatically rebuilt and redeployed via a Jenkins CI/CD pipeline on every code push, and visualised through an interactive Power BI dashboard.
Result: A complete ML + DevOps project — from raw data to live deployed API — built independently in under 2 weeks.
great job👌
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