AI Engineer building enterprise-grade agentic systems, multi-modal pipelines and intelligent automation. Turning cutting-edge research into production-ready solutions.
I'm an AI Engineer currently pursuing my Master's in Artificial Intelligence at The University of Edinburgh. My work lives at the intersection of cutting-edge research and real-world enterprise AI.
At Prodapt's NextGen Labs (R&D), I was part of a team of 50+ developers focused on researching and integrating cutting-edge GenAI tools into enterprise workflows. I personally built 30+ modular AI agents covering everything from voice navigation to medical data digitisation.
Agentic AI, LLM orchestration, RAG, Vision-Language Models, NL2SQL — applied to real-world problems.
English (Professional · IELTS C1) · Hindi (Native) · Japanese (Elementary)
From dissertation research to hackathon finalists — building AI that matters.
Agentic chatbot that translates natural language queries into SQL to retrieve live data from the IUPHAR Guide to Pharmacology PostgreSQL database — serving academic researchers and drug discovery teams. Evaluating LangGraph vs CrewAI pipelines with a PostgreSQL MCP server for schema-aware access.
AI-powered Chrome extension with three real-time tools: voice-controlled agentic navigator, social cue coaching assistant, and autonomous documentation engine. Multimodal pipeline combining Whisper + GPT-4o Vision for live lecture capture. Low-latency architecture using WebSockets and GPT-4o function calling.
Fine-tuned & benchmarked CLIP, BLIP, BLIP-2, OFA on FashionGen dataset using LoRA, full fine-tuning, and mapping-network tuning. Accelerated training 250%+ via multi-GPU parallelisation. Unified evaluation across CIDEr, BLEU-4, METEOR, ROUGE-L.
LangGraph-orchestrated agent interpreting natural language instructions and executing them via MoviePy. Trim, crop, mute/bleep, blur, generate subtitles, and translate — all through chat. Deployed as a production API endpoint for enterprise use.
Trained YOLOv8 from scratch on a combined Kaggle + Roboflow dataset spanning 59 unique traffic sign classes. Deployed as a real-time Streamlit app with live camera input for detection.
LangGraph-orchestrated multi-agent system: CrewAI for billing, AutoGen for troubleshooting, LangChain for recommendations. LlamaIndex managed hybrid SQL + vector retrieval from telecom docs and SQLite DB.
Selected among top finalists from 3,000+ participants across Prodapt in a multi-stage AI innovation competition. Competed in the final round against the best in the company.
Placed Top 8 at the University of Edinburgh's AccessAI Hackathon, building a real-world AI accessibility solution for disabled users — competing against 35+ teams from across the university.
Personally designed and deployed 30+ modular AI plugin agents as production API endpoints across diverse enterprise client environments at Prodapt R&D — spanning voice, vision, data, and automation.
I'm open to AI research collaborations, internships, and interesting projects. Connect on LinkedIn or send me a message — no spam, just good conversations.