Kartavya Raikwar — AI Engineer & Flutter Developer

Projects

What I've Built

01Featured

AI Loan Risk Prediction System

Trained a model, built an API, and shipped an Android app — all connected, all working. End-to-end ML pipeline from raw financial data to live mobile prediction.

0.91

F1-Score

10K+

Records

1K+

API Calls

Cleaned and prepared 10,000+ real financial records
Classification model trained to F1-score of 0.91
FastAPI backend with async endpoints + PostgreSQL logging
Flutter Android app with live prediction API calls
Stress-tested with 1,000+ API requests

PythonFastAPI Scikit-learnPostgreSQL FlutterRender

View on GitHub

Demo Video

Watch Demo

02

Neon Beats — Flutter Music App

Full-featured Android music streaming app handling 50,000+ tracks. BLoC architecture, lazy loading, and smooth pagination for seamless playback.

50K+

Tracks

BLoC

Architecture

BLoC state management for clean UI/logic separation
Lazy loading + pagination across 50,000+ tracks
Optimised list rendering for zero-lag playback
Firebase backend for real-time data sync

FlutterDart BLoCFirebase

View on GitHub

App Demo

Watch Demo

03Live

Diabetes Prediction — Live Web App

Enter health data, get a risk prediction instantly. Working ML model deployed as a web app — FastAPI backend, Streamlit UI, accessible right now from any browser.

0.89

F1-Score

Live ✓

Deployed

Classification model with cross-validation + StandardScaler
FastAPI backend for real-time inference
Streamlit UI — no technical knowledge needed
Deployed on Streamlit Cloud

PythonFastAPI Scikit-learnStreamlit

Live Demo GitHub

Live App

🧠 Diabetes AI · Streamlit App

Open Project

04Internship

AnemiaSense — Healthcare ML System

Built during SmartBridge ML internship on real clinical data. 5,000+ records, full feature engineering pipeline, FastAPI backend, Streamlit UI for clinical team use.

5K+

Records

Live ✓

Deployed

Processed 5,000+ real clinical records with Pandas + NumPy
Feature engineering + StandardScaler pipeline
FastAPI REST backend for real-time inference
Streamlit UI designed for clinical team use
Evaluated with F1-score + confusion matrix

PythonFastAPI PandasNumPyStreamlit

Live Demo GitHub

Live App

🩺 AnemiaSense · Streamlit App

Open Project

Behind The Code

The Story So Far

"I don't just build models. I build systems people rely on."

I'm Kartavya — I don't just code, I ship. From ML models to Flutter apps, I turn raw data into real, usable systems. Idea → AI → API → App. I build the full pipeline.

Started with basic Python, confused like everyone else. While others were learning syntax, I was pushing to build real things. Faced bugs, deployment errors, failed models — kept going anyway.

Built full ML systems from dataset to live app. Healthcare problems. Fintech problems. Not tutorials — real data, real pipelines, real results you can open right now.

I don't chase perfection, I chase execution. That's why I move faster than most.

Verified Internship

Machine Learning Engineer Intern

SmartBridge

Nov 2025 — Jan 2026 · Remote

● Open to Internships

AI/ML · Flutter Development

3rd year CS · Bhopal, India

PythonFastAPI Scikit-learnFlutter PostgreSQLDocker FirebaseStreamlit

Tech Stack