Our Projects

At Negarit Systems, we deliver innovative solutions that drive impact. From cutting-edge web applications to AI-powered platforms, our portfolio showcases our commitment to excellence and our ability to transform ideas into reality. Each project represents our dedication to creating scalable, user-centric solutions that make a difference.

AI Powered Healthcare

HealthSync

An AI-powered medical platform designed to digitize the healthcare field. It connects patients and doctors in a seamless and efficient manner. The platform leverages artificial intelligence to enhance medical diagnosis, streamline appointment scheduling, and provide educational resources for users. (The project included engagement with external individuals)

Key Features:

Appointment Scheduling for patients
Doctor and patient live chat
Doctor Rating
AI-Assisted Diagnosis
Educational Blogs

Technologies:

NextJs
NextJs
Express
Express
MongoDB
MongoDB
Tailwindcss
Tailwindcss
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Blockchain, Web Development

Terrachain

A blockchain-based land management system enabling land registration, user registration, and secure land transfer/sale with transparency and accountability.

Key Features:

Land registration
User registration
Secure Land Transfer/Sale
Web UI
Hybrid Data Storage, On Chain & Offchain

Technologies:

NextJS
NextJS
H
Hardhat
R
Remix
M
Metamask
Web Application

Rhythmix

A full-stack music app with playing, uploading, searching and deleting capabilities. Implemented clean architecture principles and seamless state management.

Key Features:

Music Play & Navigation
Favourite songs
Music Upload/Delete

Technologies:

React
React
GO
GO
MongoDB
MongoDB
RTK
RTK
VoyageGuard
Mobile App Development

VoyageGuard

IoT-based vehicle tracking system. It utilizes GPS, ELM327 (OBD2), and ESP32 for real-time monitoring of asset location and condition, incorporating machine learning for predictive maintenance.

Key Features:

Vehicle tracking with GPS
Vehicle health Monitoring
Geo-fencing alert

Technologies:

React Native
React Native
NestJS
NestJS
TypeORM
TypeORM
R
Random Forest Model
Machine Learning + Computer Architecture

Evidence-Based Static Branch Prediction with Deep Learning

Developed a Graph Neural Network (GNN)-based model to enhance branch prediction accuracy for hard-to-predict branches in modern processors, leveraging LLVM IR and XFGs. We were able to process a diverse program corpus, achieving a significant reduction in miss rates compared to traditional heuristic-based predictors

Key Features:

Computer Architecture
Machine Learning

Technologies:

Python
Python
PyTorch
PyTorch
PyTorch Geometric
PyTorch Geometric
LLVM
LLVM

Have a Project in Mind?

Let's collaborate to bring your vision to life with our proven expertise and innovative approach.