Portrait of Dhruv Motaval

Vadodara, Gujarat, India

Dhruv Motaval

AI Developer / GenAI, LLM & Agentic Applications

I build RAG systems, LLM agents, and voice pipelines — from PDF chunking and vector retrieval up through tool-calling agents and phone calls handled end to end. I like understanding how AI actually works under the hood and turning new ideas into real, working systems.

B.Tech, Artificial Intelligence · Parul University · 2026 Open to GenAI / AI Engineer roles Relocation OK

Skills

What I work with

Grouped the way I'd actually explain the stack out loud: language, then the GenAI layer, retrieval underneath it, and the backend that ships it.

Languages
Python SQL JavaScript
LLM & GenAI
LangChain LangGraph LCEL Pipelines RAG Systems Agents & Tool Calling Multi-Provider LLM Routing LangSmith Prompt & System-Prompt Design OpenAI API Groq API Ollama
AI Models Used
Llama 3.3 70B Qwen GLM GPT Claude (Sonnet, Opus) DeepSeek Whisper
Retrieval & Vector
ChromaDB Sentence Transformers Embeddings Semantic Search Document Chunking Ingestion Pipelines
Backend & Databases
FastAPI REST APIs SQLAlchemy SQLite PostgreSQL
Cloud, DevOps & Testing
Docker Cloud-Native Architecture GitHub Actions (CI/CD) Pytest Hugging Face Spaces Railway Netlify Git Linux (Ubuntu, Arch)
ML & Data
Scikit-learn Logistic Regression AdaBoost Random Forest XGBoost Pandas NumPy Model Evaluation (ROC-AUC, F1)
Speech & NLP
Whisper spaCy Multilingual NLP Intent Recognition Streamlit Gradio Chatbot Development Dashboard Development

Background

B.Tech in Artificial Intelligence (2026), Parul Institute of Technology, Vadodara, CGPA 7.12/10, on top of an earlier diploma in Computer Engineering.

Core stack

Python, LangChain, LangGraph, FastAPI, ChromaDB, Groq/OpenAI APIs, Sentence Transformers, Docker.

Right now

Interviewing for GenAI / AI developer roles, based in Vadodara, open to relocating for the right one.

Experience

Where I've worked

Web Developer Internship

iWebwala
Jan 2026 – Mar 2026
  • Delivered a production website for a solar panel installation company, managing the complete deployment lifecycle including domain registration and DNS configuration through Hostinger and deployment on Netlify.
  • Developed an AI-powered voice assistant for restaurant reservations and takeout ordering, automating customer interactions over live phone calls.
    • Integrated Twilio Voice for telephony, Whisper for speech-to-text, and ElevenLabs for text-to-speech to build a real-time conversational pipeline, deployed on Railway.

Currently Building

NomadicOS, Local-First AI Runtime

A local-first AI runtime for connecting LLM reasoning, memory, tools, and controlled OS actions through a structured execution layer.

NomadicOS, Local-First AI Runtime

actively building

A local-first runtime that connects LLM reasoning to memory, tools, and controlled OS execution.

Python LangGraph Ollama llama.cpp GGUF Pydantic
keyword overlap: 0%

Separates LLM reasoning from structured Action IR validation, authorization, OS execution, and evidence-based goal verification. Implements controlled Windows execution with owner authorization, revocation epochs, single-use authorization, filesystem confinement, structured terminal execution, and process-tree cleanup. Uses structured object-type memory and RAG for persistent context and knowledge retrieval.

Validation: 203-test regression suite, 7 live local-model tests, Ruff clean, formatting clean, and mypy clean.

Projects

What I've actually shipped

Expense Claims System

A role-based expense workflow from receipt upload through approval and finance reporting.

Next.jsTailwind CSSFastAPIPostgreSQLSQLAlchemyAWS S3Gemini Vision
keyword overlap: 0%

Built the receipt-to-payment workflow across the frontend, API, database, and storage layers. Backend rules cover role and team access, claim-state transitions, manager self-approval prevention, duplicate-receipt warnings, duplicate-payment blocking, monthly limits, and audit events. Receipt extraction creates an editable draft; payment is simulated and demo authentication is not production-grade.

ExplainOps — AI Incident Triage

Three simulated event streams become an explainable, ranked incident queue.

FastAPIScikit-learnLangChainGroqSQLiteGitHub Actions
keyword overlap: 0%

Fuses simulated ticket, log, and chat inputs; ranks incidents with a Logistic Regression model and a deterministic weighted fallback. Groq/LangChain generates grounded explanations for the top five, while false-positive feedback adjusts per-service bias and model weighting. The end-to-end pipeline is tested and runs in GitHub Actions.

ZENO — Valorant Stats & Guides

A server-rendered gaming product with player lookup, stats pages, leaderboards, and guides.

Node.jsExpress.jsMongoDBMongooseEJSBootstrapAxios
keyword overlap: 0%

Built Express routes and EJS views for player profiles and match history, leaderboards, maps, weapons, agent guides, and pro-player settings. MongoDB/Mongoose models back application data, while Axios integrates external Valorant data. Authentication code is basic configuration and middleware scaffolding, not a hardened auth system.

RAG Document Q&A & Retrieval Evaluation

Document-grounded answers with page citations and a reproducible retrieval evaluation.

FastAPIQdrantBM25 + RRFCross-encoderSentence TransformersGroqLangSmithStreamlit
keyword overlap: 0%

Implemented dense and BM25 hybrid retrieval with Reciprocal Rank Fusion, cross-encoder reranking, page-level citations, and a grounded not-found response. On the repository's 29 answerable golden-set questions, the full pipeline reports Recall@4 1.000, MRR 1.000, and NDCG@4 1.000 at about 298 ms evaluation latency; this is a small test set, not a production-scale benchmark.

Real-Time Multilingual Call Resolution

Transcribes support calls and routes them with explicit, deterministic rules.

FastAPILangGraphWhisperspaCyGroqStreamlit
keyword overlap: 0%

A four-node LangGraph workflow uses local Whisper transcription, spaCy language detection, keyword-based intent recognition, and deterministic support routing. Groq generates audit explanations but does not choose the route. FastAPI exposes audio processing, audit-history, and event-replay endpoints, with a Streamlit dashboard for review.

Stroke Risk Prediction API classical ML

A trained classifier served through a documented prediction API.

PythonScikit-learnPandasNumPyFastAPIDocker
keyword overlap: 0%

Trained a stroke-risk classifier with preprocessing, feature engineering, and class-imbalance handling on a public patient dataset. FastAPI exposes a POST /predict endpoint and the repository includes a Dockerfile for local containerized execution. The model is a demonstration, not a clinical diagnosis or medical decision tool.

Also built

Additional engineering projects

NomadicOS — Local-First AI Orchestration

Python orchestration runtime with typed action validation, owner authorization, model routing, bounded recovery, and evidence-backed verification. Version 0.2.0 is a controlled-execution foundation; desktop control and semantic memory are still in development.

GitHub →

Self-Evaluating Lesson Generator

LangGraph workflow generates a lesson, checks it against a strict six-part rubric, revises failed checks within a retry limit, and stores recurring pitfalls in SQLite memory. The run log records failures honestly instead of silently marking every output successful.

GitHub →

Northstar One — AI Sales Agent

FastAPI chatbot for lead qualification and objection handling with JSON tool schemas and provider fallback. Site-visit booking is simulated, session memory is in-memory, and the demo does not include authentication.

GitHub →

AI Meeting Minutes Generator (Auto-MOM)

Converts meeting audio to a formatted PDF using Whisper transcription, spaCy entity extraction, and ReportLab. A Gradio/Hugging Face demo is available.

GitHub →Live Demo →

Education

Academic background

Parul Institute of Technology, Vadodara

2023 – 2026

B.Tech, Artificial Intelligence · CGPA 7.12 / 10

Publication: "Limits of AI in Software Development: Empirical Analysis of AI vs Human Engineers," ISJEM Journal, April 2026.

A. Y. DadaBhai Institute of Technology, Kosamba

2019 – 2023

Diploma, Computer Engineering · CGPA 7.91 / 10

Contact

Let's talk

Open to GenAI / AI developer roles, based in Vadodara, happy to relocate for the right one.