orchestrating agentic systems at scale.
Mastering state-of-the-art architectures: driving high-performance deep learning models, autonomous multi-agent orchestration, and production-grade backend security.
Professional Registry // Bio
Orchestrating Complex Agentic Operations.
Operating at 100% capacity in Artificial Intelligence & Machine Learning at L.D. College of Engineering. I build secure, high-performance deep learning architectures and tool-calling agent systems, backed by nature-inspired optimization algorithms and strict cryptography rules.
Academic Credentials & Foundations
Driving deep research in Neural Networks (backpropagation, activation optimization, multi-layer perceptrons), nature-inspired swarm intelligence algorithms, socket networking paradigms, and cryptosystem implementations.
Active Hero Projects
LLMBench Eval
A production-grade AI quality engineering platform designed to benchmark Large Language Models, evaluate prompt templates, detect regression anomalies, and optimize LLM query costs. Powered by an asynchronous Celery and Redis pipeline with LLM-as-a-Judge evaluations and automated failure diagnostics.
Luminate AI RAG
> parsing arXiv research literature...
> RAPTOR index: built hierarchical tree [ok]
> running CRAG relevance grader...
> grading nodes: ambiguous context [fallback active]
> corrective query arXiv API: fetch deepseek-v3...
> final synthesis: context resolved [100% correctness]
A client-side serverless search assistant designed to synthesize research papers. Resolves context fragmentation by building a RAPTOR hierarchical clustering index and leverages Corrective RAG (CRAG) to fall back on live arXiv literature when local context is insufficient.
RepoMind Agent
An AI-powered codebase onboarding assistant that analyzes public GitHub repositories to generate interactive dependency graphs, architectural designs, and custom developer onboarding checklists — powered by a self-correcting multi-agent LangGraph pipeline.
MAC-SPOT CLI
> mac-spot --explain "IndexError: list index out of range"
> analyzing stack trace and source context...
> fetch: Gemini API model response [ok]
> executing code check: no syntax errors
> interactive chat mode: initialized
A production-ready macOS command-line assistant built in Python and powered by Google's Gemini API. Provides developers with real-time CLI debugging, error explanations, code reviews, automated Git commit message generation, and conceptual coding cheat sheets.
Lead-Bot AI
An autonomous conversational agent built for portfolios and SaaS interfaces to qualify leads, answer project/technical FAQs, and capture contact signals. Powered by a local rule-based intent router and vector matching algorithms for zero latency.
Autonomous Engagement // Conversion Matrix
Qualify Leads 24/7 Autonomous Agent.
Lead-Bot AI is a custom conversational assistant designed to capture, qualify, and convert portfolio visitors in real-time. It acts as an interactive sales layer—answering technical questions, showing credentials, and capturing project briefs.
Get in touch // Start a conversation
Let's talk projects.
Have an active mission, deep learning research, or an autonomous agent pipeline you want to co-engineer? Transmit a signal, and let's go beyond limits.