Sai Sri Abhiram Nelluri

CEO

Noida, Uttar Pradesh, India0 mo experience
AI EnabledAI ML Practitioner

Key Highlights

  • Developed AI-powered telemedicine platform supporting 500+ patients.
  • Engineered real-time ANPR system with 91% accuracy.
  • Optimized database queries reducing search latency from 1.2s to 80ms.
Stackforce AI infers this person is a Backend and AI Engineer with experience in scalable systems and real-time applications.

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Skills

Core Skills

Generative AiNlpMachine LearningComputer VisionRobotic Process AutomationAi Engineering

Other Skills

GenAILLMsYOLOv8SORTEasyOCRFlaskRobotic Process Automation (RPA)Backend DevelopmentRetrieval-Augmented Generation (RAG)Scalable SystemsArtificial Intelligence (AI)Full-Stack DevelopmentData Structures & AlgorithmsSystem Design

About

I’m a Computer Science undergraduate at Bennett University passionate about building scalable backend systems, real-time applications, and AI-powered products that solve real-world problems. My work focuses on the intersection of backend engineering, machine learning, and distributed systems. I enjoy designing high-performance architectures, optimizing data pipelines, and building intelligent systems that operate reliably at scale. Some of my key projects include: • MediCare Pro — an AI-powered telemedicine platform with WebRTC-based video consultations supporting 500+ concurrent patient records with <150ms latency, built using microservices architecture with Node.js, Python, and MongoDB. • HireSphere — a campus recruitment platform that processes 500+ resumes using AI-driven parsing pipelines, with real-time notifications handling 1000+ application events daily and optimized database queries reducing search latency from 1.2s to 80ms. • LegalNexus — a Retrieval-Augmented Generation (RAG) legal AI assistant using FAISS vector search and NLP pipelines to answer IPC queries in under 300ms while improving query relevance by 40%. During my internship at ITC Limited, I developed a real-time Automatic Number Plate Recognition (ANPR) system using YOLOv8, SORT, and EasyOCR that achieved 91% vehicle tracking accuracy in production while reducing ID-switch errors by 30%. I have also gained hands-on experience with generative AI and LLM workflows through the NASSCOM x Google GEN-AI program, building applications using Gemini APIs, FastAPI, and modern NLP pipelines. Beyond projects and internships, I actively strengthen my computer science fundamentals through Data Structures & Algorithms (300+ problems solved) and system design concepts across operating systems, networking, and distributed systems. Technical Interests: Backend Engineering • AI/ML Systems • Retrieval-Augmented Generation • Real-Time Systems • Microservices Architecture • Scalable Distributed Systems Tech Stack: Python • Java • C++ • JavaScript • Node.js • React • Express.js • Flask • MongoDB • MySQL • FAISS • WebRTC • Socket.IO • REST APIs I’m always excited to collaborate on innovative projects in backend engineering, AI systems, and scalable real-time platforms.

Experience

Smartinternz

NASSCOM | Google GEN-AI

Jun 2025Jul 2025 · 1 mo · Remote

  • Key accomplishments include:
  • Developed innovative text generation and summarization workflows utilizing Gemini and FastAPI that improved processing efficiency by 25%, streamlining data handling for AI applications.
  • Engaged in hands-on labs focused on Generative AI technologies including LLMs and NLP techniques that enhanced understanding of real-world applications in chatbot development.
  • Gained practical experience with BERT and GANs while constructing deep learning pipelines, contributing to a significant reduction in model training time by 15% through optimized processes.
GenAILLMsGenerative AINLP

Itc limited

Machine Learning Intern

Jun 2025Jul 2025 · 1 mo · Bhadrachalam, Telangana, India · On-site

  • Key accomplishments include:
  • Engineered a real-time Automatic Number Plate Recognition (ANPR) pipeline utilizing YOLOv8, SORT, and EasyOCR, achieving an impressive 91% vehicle tracking accuracy in a production environment.
  • Optimized hyperparameters for the SORT algorithm, successfully reducing ID-switch errors by 30% during challenging occlusion conditions to enhance overall tracking reliability.
  • Developed a Flask-based video processing system that streamlined vehicle detection and license plate recognition processes while ensuring efficient data handling and user interaction.
  • Implemented timestamped logging for vehicle entry and exit events, which improved tracking consistency by 18%, contributing to more reliable data analytics for traffic management.
Machine LearningYOLOv8Computer Vision

Robotics process automation club

Technical Co-Head

Sep 2024Dec 2024 · 3 mos

  • Key accomplishments include:
  • Spearheaded the development of multiple robotics process automation projects that enhanced operational efficiency by automating routine tasks for club members while reducing processing time by 40%.
  • Collaborated with a team of 10 peers to tackle complex technical challenges using AI technologies, driving innovative solutions that improved project outcomes and engagement levels by 25% during the semester.
  • Organized workshops focused on RPA tools and techniques, increasing participation by 60% compared to previous sessions, fostering a collaborative learning environment among members interested in automation technologies.
Robotic Process Automation (RPA)AI EngineeringRobotic Process Automation

Education

Bennett University

Bachelor of Technology - BTech — Computer Science

Sep 2023Sep 2027

Narayana Institute

Apr 2020Jul 2022

Bhadrachalam Public School & Jr. College

May 2008Mar 2020

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