Sai Nivedh V

Sai Nivedh V

AI & Full Stack Developer

Profile Picture

I'm a passionate AI & Full Stack Developer currently pursuing my B.Tech. in CSE with a specialization in Artificial Intelligence at Amrita Vishwa Vidyapeetham. With a strong foundation in various programming languages and cutting-edge technologies, I'm dedicated to creating innovative solutions that push the boundaries of what's possible in tech.

My expertise spans across Machine Learning, Web Development, and DevOps, allowing me to tackle complex projects from multiple angles. I'm always eager to learn and apply new technologies to solve real-world problems.

Skills

Languages

py
java
c
js
kotlin
flutter
html
css
matlab
go

Machine Learning & AI

tensorflow
pytorch
sklearn
LangChain
LangChain
LlamaIndex
LlamaIndex
Haystack
Haystack
CrewAI
CrewAI
SnowFlake
SnowFlake
LangGraph
LangGraph
Unsloth
Unsloth

Databases

mongodb
Neo4j
Neo4j
redis
firebase
supabase
postgres
mysql

Web Development

django
flask
fastapi
react
nextjs
tailwind
REST API
REST API
graphql
express
vite
bootstrap
materialui

DevOps

docker
jenkins
kubernetes
kubernetes
CI/CD Pipelines
CI/CD Pipelines
heroku
vercel
netlify

Cloud & Code Management

git
github
githubactions
aws
gcp
azure
postman
selenium

Other Tools

clion
vscode
pycharm
ubuntu
kali
raspberrypi
neovim
obsidian
anaconda
androidstudio

Experience

Software Development Intern

Binari Intelligence System Private Limited

Nov 2024 – Jan 2024

Worked on cutting-edge AI and software development projects.

Binari Intelligence System Private Limited

Projects

Accessible AI - Sign Language Mapping

Engineered an innovative application for generating Indian Sign Language (ISL) videos from diverse media formats using Google Cloud Speech-to-Text for real-time transcription.

Google CloudNLPMoviePy

VerifyIt - Chrome Extension

Engineered a high-speed fact-checking Chrome extension using Flask, Google Custom Search API, Crawl4AI, and Gemini.

FlaskGoogle Custom Search APICrawl4AIGemini

Deepfake Detection - Intel OneAPI Challenge

Designed and implemented a deepfake detection application using the ResNeXt-50 model, trained on the Celeb-DF (v2) dataset with 6,000+ samples, achieving 85% detection accuracy.

ResNeXt-50Intel oneDNNOpenVINO

Femineh - Full stack Healthcare application

Developed a full-stack RAG application for personalized diet plan recommendations and food component analysis.

ReactFastAPILangChainCrawl4AIGroqOpenAIChromaMongoDB Atlas

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