Govindu Sai Anish

Govindu Sai Anish

AI/ML & Backend Software Engineer | B.Tech CSE (AI/ML) Student


About

Computer Science student specializing in AI/ML and backend engineering, with experience building Spring Boot microservices, RAG systems, and multimodal AI agents. Skilled in Java, C++, Python, SQL, Spring Boot, and distributed systems, with a strong focus on scalable backend architectures and intelligent applications.

Skills
Java
Python
JavaScript
Docker
Node.js
React
LangChain
MongoDB
PostgreSQL
Experience

MERN Stack Developer

Edunet Foundation

Jun 2025 to Jul 2025
  • Developed a full-stack real-time healthcare platform using the MERN stack, enabling distributed inventory
  • sharing and live communication between hospitals and blood banks.
  • • Engineered smart dashboards for 8+ blood types and 5+ organ categories with 99.5% accuracy, and reduced
  • emergency response time by 65% through faster donor-hospital coordination and request handling.
  • • Implemented a geo-based donor matching engine (within 300 km), boosting match success by 50%.
Projects

Multimodal AI Agent for Autonomous Computer Use

• Developing a vision-language agent for autonomous GUI interaction using multimodal reasoning, GUI understanding, grounding, and action prediction. • Designing GUI grounding and action prediction to map instructions to UI elements and executable actions with error recovery. • Fine-tuning pretrained vision-language models with GUI-specific data and evaluating task success.

Python
PyTorch
Hugging Face Transformers
Vision-Language Models (VLMs)
OpenCV
OCR
OSWorld

QuizApp Microservices - Spring Boot Microservices Project

Developed a Java Spring Boot microservices-based Quiz Application with independent Quiz, Question, API Gateway, and Eureka Service Registry services. • Implemented REST APIs and inter-service communication using OpenFeign, with Eureka-based service discovery and API Gateway routing for distributed service communication. • Integrated MySQL with JPA/Hibernate using layered Controller, Service, Repository, and Model architecture.

Spring Boot
Hibernate
MySQL
Eureka
OpenFeign

CortexRAG – Knowledge Base AI Chatbot (RAG System)

• Designed and implemented a production-grade RAG system over PDF, DOCX, and TXT documents, improving answer relevance by 35% and reducing hallucinations through grounded responses. • Engineered a hybrid retrieval pipeline (FAISS + BM25) with cross-encoder reranking (MS MARCO MiniLM), increasing retrieval precision by 25% and reducing irrelevant context passed to the LLM by 40%. • Developed an end-to-end system with LLM-based query expansion and a FastAPI + React architecture, achieving sub-2s response latency and improving retrieval coverage by 20% for ambiguous user queries.

Python
LangChain
FAISS
BM25
MS MARCO
Education

B.Tech

SRM AP University · 8.93

Oct 2023 to May 2027