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Just joined Contra 👋
I’m a Flutter and full-stack engineer focused on building polished mobile apps, scalable APIs, payment flows, and startup MVPs.
I work across Flutter, NestJS, Node.js, integrations, and product-focused development, helping founders and teams turn good ideas into reliable products people can actually use.
Currently open to collaborating on mobile apps, fintech products, internal tools, and early-stage MVPs.
Glad to be here. Let’s build something useful.
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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Just published a new case study on Contra for Tiun.io 🚀
A 3-minute product launch video combining UI animation, motion graphics, and dynamic transitions to showcase their backend infrastructure platform.
Check it out and let me know what you think💭
SupportFlow AI is a customer support management system built with Python, PySide6, FastAPI and PostgreSQL.
It helps teams manage customer requests, assign priorities and responsibilities, track conversations, and generate AI-assisted response suggestions while keeping a human in control of the final reply.
I built the application structure, interface, backend integration, database workflows, API layer and automated testing.
The conversation-revision idea sounds useful. I would also check that revision on the server when accepting the send, so a message arriving between review and click cannot slip through. Mark the draft stale while keeping the human edits visible. Two useful regression cases: a...
Agri Guard is a full-stack web application that helps farmers identify plant diseases instantly using AI. Users can upload a photo of an affected plant or describe symptoms in text, and the app returns a diagnosis along with a verified treatment plan.
What I built:
A clean, dark-themed landing page with a hero section, trust badges, feature highlights and clear call-to-action buttons (Get Started, Login to Dashboard)
A Node.js and TypeScript backend with REST API routes, utility modules and environment-based configuration
AI integration for image analysis and text-based diagnosis through the OpenRouter API
A disease database with treatment recommendations, plus scripts to extend it with new diseases
Login and dashboard flow for returning users
My focus: a clear, conversion-friendly landing page, readable typography, consistent spacing and a responsive layout that works on both desktop and mobile.
How do you connect the model's diagnosis to the treatment database? Does it have to match a known disease entry before showing a treatment, or can the model generate recommendations outside that list?
