class HenilBhavsar:
def __init__(self):
self.name = "Henil Bhavsar"
self.role = "AI / ML Engineer"
self.location = "Ahmedabad, Gujarat, India 🇮🇳"
self.education = "B.E. Computer Engineering — LJ University (2022–2026)"
self.company = "X-Byte Enterprise Solutions (Jr. Python Developer)"
self.product = "Founder @ Ragora.ai — live AI chatbot SaaS, 150+ users"
self.specialties = [
"LLM Fine-Tuning (QLoRA / 4-bit)",
"RAG Architectures & Vector Databases",
"Production FastAPI Backend Systems",
"Generative AI & Conversational Agents",
"Large-scale Data Pipelines (13M+ records)",
"AI Automation Workflows (n8n)",
]
self.stack = {
"core" : ["Python", "PyTorch", "LangChain", "FastAPI"],
"ai_ml" : ["HuggingFace", "Transformers", "Scikit-learn", "TensorFlow"],
"data" : ["MongoDB", "PostgreSQL", "Redis", "Vector DBs"],
"infra" : ["Docker", "AWS", "Git", "Linux"],
}
self.currently_exploring = [
"Advanced RAG + Agentic Architectures",
"Distributed LLM Inference (vLLM)",
"Multi-modal AI Systems",
]
def philosophy(self) -> str:
return "Models are just the beginning — deployment is where magic happens."
def status(self) -> str:
return "🟢 Open to full-time AI/ML roles & research collaborations"| 📦 Records Processed | 🤖 AI Projects Shipped | 🧬 Params Fine-Tuned | 👥 Live Product Users | 🏅 Certifications |
|---|---|---|---|---|
| 13M+ | 9+ | 7B | 150+ | 6+ |
🧠 AI / ML / GenAI Stack
Machine Learning · Deep Learning · NLP · Generative AI · RAG Systems · QLoRA Fine-Tuning · Model Deployment · AI Automation Agents
⚡ Backend & Infrastructure
RESTful APIs · WebSockets · OAuth2 & JWT · Async Programming · Containerization · Cloud Deployment
🗄️ Data & Databases
Vector Databases · ETL Pipelines · SQL & NoSQL · Statistical Modeling · Data Visualization
|
Junior Python Developer · Mar 2025 – Sep 2025 📍 Ahmedabad, India (On-site) |
Tech Used:
|
🚀 Key Achievements:
- Scraped and processed ~13M records from a Saudi food delivery platform, building reliable end-to-end automation pipelines
- Developed structured APIs and data pipelines delivering analytics-ready data to enterprise clients
- Automated weekly scraping workflows for Russian e-commerce and Indian quick commerce platforms
- Performed cross-platform data mapping and transformation ensuring 99% consistency across client systems
- Collaborated directly with clients on requirements, delivery timelines, and data quality standards — cutting decision-making time by 30%
Ragora.ai — Your website visitors are leaving because nobody replies instantly. Ragora turns your documents into a smart AI assistant — trained on your data, embedded on any website, live in under 3 minutes.
|
Core Capabilities:
|
Tech Stack:
|
Fine-tuned Mistral 7B using QLoRA (4-bit quantization) on curated domain-specific datasets. Achieved measurable accuracy improvements over the base model on medical diagnosis, legal reasoning, and financial analysis tasks. Highlights:
|
📊 DataSage
An intelligent data analysis assistant that understands natural language — upload any CSV, ask questions in plain English, and get instant charts, KPIs, and insights. 50% reduction in manual analysis time. Highlights:
|
🧠 DocMind
Upload any PDF and have an AI-powered conversation with it. DocMind uses a production RAG architecture with vector search to retrieve precise, context-aware answers — not hallucinations. Highlights:
|
🩺 CuraAI
ML-powered health assistant predicting diseases from symptoms (text or voice input) with 99% model accuracy. Delivers personalized medication, workout, and diet recommendations. 35% improvement in user health adherence. Highlights:
|
Three production AI agents: automated code reviewer, YouTube publisher, and Instagram Reels poster — all driven by intelligent n8n workflow automation.
|
End-to-end ML experimentation platform for building, training, evaluating, and deploying models — no boilerplate required.
|
ML + NLP system analyzing facial expressions and text to identify emotions in real time using deep learning.
|
|
🤖
Building Generative AI Apps with Python
|
🧠
Building with the Claude API
|
⚙️
Machine Learning Using Python
|
|
☁️
AWS Cloud Technical Essentials
|
📊
Exploratory Data Analysis for ML
|
🌐
HTML, CSS & JavaScript
|
Open to full-time roles, freelance AI projects, and research collaborations
| 🌐 Portfolio | 🐙 GitHub | ||
|---|---|---|---|
| henilbhavsar164@gmail.com | henil-bhavsar | portfolio.in/henil | Henilll |
