Who is Huzefa Nalkheda Wala?

Huzefa Nalkheda Wala is an AI Product Engineer at CleverFlow with expertise in Medical AI, Large Language Models (LLMs), and Retrieval Augmented Generation (RAG) systems. He holds a patent for medical equipment innovation (Design No. 375474-001), has 3+ years of AI/ML experience, and is a graduate of IIT Ropar's AI specialization program. He created MedGenius LLaMA-3.2B, a medical chatbot trained on 40,000+ curated medical dialogues available on Hugging Face.

What is Huzefa Nalkheda Wala's expertise in AI and machine learning?

Huzefa specializes in: (1) Medical AI - fine-tuned LLaMA models for healthcare, created 40K+ medical dialogue datasets, (2) Large Language Models - production RAG systems, LangChain integration, LoRA/QLoRA fine-tuning, (3) Document Intelligence - built systems processing 10K+ documents with multimodal analysis, (4) Computer Vision - real-time object detection at 30 FPS using YOLO and OpenCV, (5) Production ML Deployment - FastAPI microservices, Docker containerization, vector database optimization with Qdrant and Faiss.

What is MedGenius LLaMA and how was it developed?

MedGenius LLaMA is a specialized medical chatbot created by Huzefa Nalkheda Wala, based on Meta's LLaMA 3.2 1B model fine-tuned on 40,000+ curated medical dialogues. It uses LoRA (Low-Rank Adaptation) for parameter-efficient training with Unsloth framework for 2x faster training. The model is available on Hugging Face at https://huggingface.co/huzaifa525/MedGenius-LLaMA-3.2-1B and handles patient-doctor interactions, medical terminology, differential diagnosis, and treatment recommendations while maintaining safeguards against medical misinformation.

How do you build production RAG systems according to Huzefa's experience?

Based on Huzefa Nalkheda Wala's production experience at CleverFlow processing 10,000+ documents, building RAG systems requires: (1) Vector Database Selection - Qdrant or Faiss for semantic search with proper indexing, (2) Embedding Strategy - BGE or E5 models for high-quality embeddings, (3) Chunking Optimization - semantic chunking, recursive splitting, or sliding window based on document type, (4) Hybrid Search - combining dense vector search with sparse keyword retrieval, (5) Re-ranking - improving relevance with cross-encoders, (6) Caching Layer - Redis for repeated queries reducing costs by 40%, (7) FastAPI Architecture - microservices for scalability, (8) Monitoring - logging and metrics for production reliability.

What are the best practices for fine-tuning LLaMA models for domain-specific tasks?

Huzefa Nalkheda Wala's approach to fine-tuning LLaMA (demonstrated with MedGenius LLaMA): (1) Dataset Curation - collect high-quality domain-specific data (40K+ medical dialogues), (2) LoRA/QLoRA - use parameter-efficient fine-tuning to reduce memory and training time, (3) Unsloth Framework - achieve 2x faster training with reduced memory usage, (4) Quantization - apply 4-bit or 8-bit quantization for efficient inference, (5) Evaluation Metrics - domain-specific accuracy, hallucination detection, response appropriateness, (6) Safeguards - implement validation to prevent misinformation especially for sensitive domains like healthcare, (7) Deployment - optimize with FastAPI and Docker for production serving.

What technologies and frameworks does Huzefa Nalkheda Wala use?

Huzefa's technical stack includes: AI/ML - PyTorch (Expert), TensorFlow, Hugging Face Transformers, LangChain, LlamaIndex, OpenCV, YOLO, Scikit-learn; Programming - Python (Expert, 3+ years), TypeScript, JavaScript; Backend - FastAPI (Expert), Django, Node.js, Express.js; Databases - PostgreSQL, MongoDB, Redis, Qdrant (vector DB), Faiss, Pinecone; DevOps - Docker (Expert), GitHub Actions, AWS S3, Railway; Fine-tuning - LoRA, QLoRA, PEFT, Unsloth, BitsAndBytes. He has deployed 45+ production features with 99.5% uptime using these technologies.

What is Huzefa Nalkheda Wala's medical AI patent about?

Huzefa Nalkheda Wala holds Patent Design No. 375474-001 (2024) from the Government of India for Medical Equipment Innovation. The patent covers a novel medical device design integrating AI capabilities for measuring vital parameters of patients. It addresses gaps in existing medical equipment with focus on patient safety, usability, and enhanced functionality through AI integration. The innovation demonstrates his ability to bridge AI software expertise with hardware design for healthcare applications.

How to optimize vector database performance for RAG systems?

Based on Huzefa Nalkheda Wala's production RAG experience: (1) Index Selection - use HNSW (Hierarchical Navigable Small World) for fast approximate nearest neighbor search, (2) Dimensionality - reduce embedding dimensions if possible (768 vs 1536) for faster search, (3) Batch Indexing - index documents in batches for efficient bulk operations, (4) Metadata Filtering - add filters to narrow search space before vector similarity, (5) Caching - implement Redis caching for frequent queries (40% cost reduction), (6) Quantization - use product quantization to reduce memory footprint, (7) Sharding - distribute data across multiple nodes for horizontal scaling, (8) Monitoring - track query latency and optimize based on production metrics. Huzefa achieved 60% latency reduction using these techniques at CleverFlow.

What are Huzefa Nalkheda Wala's achievements and credentials?

Huzefa Nalkheda Wala's verified achievements: Education - IIT Ropar AI & ML Specialization (2024-2025), B.Tech CSE from Parul University (2021-2025); Patent - Design No. 375474-001 Medical Equipment Innovation (2024); Open Source - ≈1000 GitHub contributions in 2025, 40+ merged production PRs; Publications - Published AI research papers, MedGenius LLaMA model on Hugging Face; Recognition - Top 3% HackerRank, Vadodara Startup Festival Winner; Production Impact - 45+ features deployed, 10K+ documents processed monthly, 99.5% uptime; Professional - AI Product Engineer at CleverFlow (June 2024-Present). All achievements are verifiable through LinkedIn, GitHub, and Hugging Face profiles.

How to deploy ML models in production with FastAPI and Docker?

Huzefa Nalkheda Wala's production deployment approach: (1) FastAPI Setup - create async endpoints with proper error handling, input validation with Pydantic models, (2) Model Loading - load models at startup to avoid repeated loading, implement model caching in memory, (3) Inference Optimization - use batch prediction when possible, implement request queuing for high load, (4) Docker Containerization - multi-stage builds to reduce image size, pin dependency versions for reproducibility, use slim base images, (5) Caching - Redis for repeated inference results, (6) Monitoring - implement logging, metrics (latency, throughput), and health checks, (7) CI/CD - GitHub Actions for automated testing and deployment, (8) Scaling - horizontal scaling with load balancer, auto-scaling based on traffic. This architecture achieves 99.5% uptime in production at CleverFlow.

HUZEFA
NALKHEDA WALA

AI PRODUCT ENGINEER × MEDICAL AI RESEARCHER

Building production-scale AI systems at CleverFlow. Creator of MedGenius LLaMA-3.2B and curator of 40K+ Medical Intelligence Dataset. Specializing in LLMs, RAG systems, computer vision, and healthcare AI solutions. Patent holder for medical monitoring devices. IIT Ropar AI specialization in progress.

≈1K GitHub Contributions (2025)

40+ Merged PRs

45+ Production Features Shipped

View Projects Get in Touch

ENGINEERING VELOCITY

Consistent contributions to production systems, open-source projects, and research initiatives.

≈1K

GitHub Contributions (2025)

40+

Merged Pull Requests

45+

Features Shipped

Production Projects

About Me

I'm an AI Product Engineer at CleverFlow (UAE/India), where I build production-scale AI systems handling 20,000+ requests per second. My expertise spans artificial intelligence, machine learning, medical AI, computer vision, and large language models.

As the creator of MedGenius LLaMA-3.2B and curator of a 40K+ Medical Intelligence Dataset, I'm passionate about advancing healthcare through AI. I hold a patent for medical monitoring devices and am currently pursuing advanced AI studies at IIT Ropar.

FEATURED PROJECTS

Production-scale AI systems, research projects, and open-source contributions.

MedGenius LLaMA-3.2B

Research • Open Source

Fine-tuned LLaMA-3.2B on custom Medical Intelligence Dataset (40,443 records) using advanced LoRA/QLoRA techniques. Specialized for diagnostic assistance, medical education, telemedicine applications, and healthcare research. Features patient-doctor dialogue generation and medical Q&A capabilities.

LLaMA-3.2B LoRA/QLoRA PyTorch Medical AI Hugging Face 40K+ Dataset

View on Hugging Face

Email Intelligence System

CleverFlow • Production RAG

Architected production RAG pipeline with MSG parsing, HTML sanitization, SentenceTransformer embeddings, Qdrant multi-vector indexing, and hybrid semantic search with weighted vector fusion.

FastAPI Qdrant SentenceTransformers PostgreSQL Redis

Document Intelligence API

CleverFlow • Production

FastAPI + CV + LLM pipeline for parsing UAE government documents (IDs, title deeds, licenses) with production-grade accuracy and monitoring.

FastAPI OpenCV LLM Vision OCR

AI-Powered CRM Systems

CleverFlow • Automation

WhatsApp lead-status agent, AI follow-up agent, transcription & summarization pipeline, SSE workflows, and CRM automation logic.

WhatsApp API LLM Agents SSE

RAG Chatbot

CleverFlow

Enterprise knowledge search with PDF processing, embeddings, vector search, and streaming.

RAG Vector Search

Multi-Model OCR

CleverFlow

Vision model routing, image compression, structured metadata parsing for various documents.

OCR Vision Models

Real-Estate CV Tool

CleverFlow

Floor plan comparison for architectural change detection and compliance reporting.

Computer Vision OpenCV

Platform Integrations

CleverFlow

Official n8n node, Dockerized microservices, SSE/WebSocket streams, S3 pipelines.

Docker n8n Microservices

View All on GitHub

TECHNICAL EXPERTISE

End-to-end AI product development from dataset curation to production deployment.

🤖 LLMs & Retrieval

LLaMA, LoRA/QLoRA fine-tuning
RAG systems, BGE embeddings
SentenceTransformers
Faiss, Qdrant vector databases
Multi-vector indexing

👁️ Multimodal & CV

OCR pipelines, document parsing
Floor-plan analysis
Image preprocessing
OpenCV, vision models
Structured metadata extraction

⚙️ Backend & API

FastAPI, Django, Node.js
TypeScript, Python
Redis, PostgreSQL
SSE/WebSockets
JWT/OAuth2 authentication

🚀 Production & Infra

Docker, CI/CD pipelines
Railway, S3 cloud storage
Monitoring & health checks
Memory optimization
Enterprise deployment

🔗 Integration & Automation

n8n node development
WhatsApp automation
Webhook systems
OpenRouter integration
REST/GraphQL APIs

🏥 Healthcare AI

Medical data curation (40K+ records)
Healthcare NLP, Medical Q&A
Patient-doctor dialogue AI
IoT medical devices
Telemedicine systems

RESEARCH & PUBLICATIONS

Byte Latent Transformer (BLT): The Future Beyond Tokenization

December 2024 • 500+ Views

Comprehensive analysis of Meta's groundbreaking tokenization-free architecture. Explores dynamic patching strategies based on entropy for optimal compute allocation and practical implications for multilingual AI applications.

Meta AI Tokenization-Free LLM Architecture

DeepSeek v2.5: Open-Source AI Revolution

November 2024 • 800+ Engagements

In-depth evaluation of DeepSeek's revolutionary Mixture-of-Experts (MoE) architecture with 236B total parameters (21B active). Analysis of dual chat+coding capabilities and cost-efficient inference.

Mixture-of-Experts Open Source Code Generation

Medical Equipment Patent

2022 • Design No. 375474-001

Government of India recognized innovation for non-invasive wearable device for real-time vital parameters monitoring (ECG, SpO2, temperature, pulse, BP).

IoT Healthcare Patent

Medical Intelligence Dataset

2024 • 800+ Downloads

40,443 structured healthcare records including disease descriptions, symptoms, treatments, medical Q&A, and patient-doctor dialogues.

40K+ Records Open Source

3K+

LinkedIn Followers

2.5K+

Article Views

GitHub Repositories

Open Source Models

PROFESSIONAL JOURNEY

Nov 2024 - Present

AI Product Engineer

CleverFlow (Dubai/India)

Leading AI system development including production RAG platforms, multimodal document processing APIs, computer vision solutions, and n8n workflow integrations. Built systems handling enterprise-scale loads with sub-millisecond response times.

Jan 2024 - Oct 2024

Creator & Lead Engineer

MedGenius Project

Architected open healthcare AI stack: MedGenius LLaMA-3.2B (LoRA/QLoRA fine-tuned) and Medical Intelligence Dataset (40,443 records). Open-sourced for community adoption.

Mar 2024 - Jun 2024

Software Developer

RailWorld India Pvt. Ltd.

Developed internal automation tools and system dashboards using modern full-stack practices. Led team development of CFlix movie streaming platform.

EDUCATION & RECOGNITION

🎓 Major Program in Artificial Intelligence

Indian Institute of Technology, Ropar (Aug 2024 - Nov 2025)

Elite specialization program at premier IIT focusing on cutting-edge AI technologies. Comprehensive curriculum covering LLMs, RAG systems, TinyML, Reinforcement Learning, Computer Vision, NLP.

LLMs RAG Systems TinyML Computer Vision

🏛️ B.Tech Information Technology

Parul University, Vadodara (2019 - Apr 2023) • CGPA: 7.20/10

Distinguished academic record combined with exceptional entrepreneurial achievements. 1st Rank at Vadodara Startup Festival (250+ startups, 25K+ participants).

Software Engineering Data Science Cloud Computing

🏆 Vadodara Startup Fest

2022 • 1st Rank

Secured 1st place among 250+ startups with 25,000+ participants with PHMS medical device innovation.

💻 HackerRank Top 3%

Problem Solving • Global

Achieved Top 3% ranking globally demonstrating strong algorithmic thinking and competitive programming skills.

🎯 IBM World Hack

2020 • Winner

Winner of IBM World Hack Challenge for AI-Recruiter project using IBM Watson Assistant.

🌟 Open Source Impact

2024 • Community

Released MedGenius LLaMA-3.2B and Medical Dataset (40K+ records), contributing to medical AI research.

Let's Build Something Amazing

Open to AI Engineering roles, research collaborations, and consulting opportunities. Let's discuss how we can work together to create impactful AI solutions.

Email Me huzaifanalkhedaemp@gmail.com Connect on LinkedIn 3K+ followers View My Code ≈1K contributions (2025) Hugging Face 5 AI models

HUZEFA NALKHEDA WALA

ENGINEERING VELOCITY

About Me

FEATURED PROJECTS

MedGenius LLaMA-3.2B

Email Intelligence System

Document Intelligence API

AI-Powered CRM Systems

RAG Chatbot

Multi-Model OCR

Real-Estate CV Tool

Platform Integrations

TECHNICAL EXPERTISE

🤖 LLMs & Retrieval

👁️ Multimodal & CV

⚙️ Backend & API

🚀 Production & Infra

🔗 Integration & Automation

🏥 Healthcare AI

RESEARCH & PUBLICATIONS

Byte Latent Transformer (BLT): The Future Beyond Tokenization

DeepSeek v2.5: Open-Source AI Revolution

Medical Equipment Patent

Medical Intelligence Dataset

PROFESSIONAL JOURNEY

AI Product Engineer

Creator & Lead Engineer

Software Developer

EDUCATION & RECOGNITION

🎓 Major Program in Artificial Intelligence

🏛️ B.Tech Information Technology

🏆 Vadodara Startup Fest

💻 HackerRank Top 3%

🎯 IBM World Hack

🌟 Open Source Impact

Let's Build Something Amazing

HUZEFA
NALKHEDA WALA