Building offline-first academic intelligence, mental wellness platforms, payment data tools, local voice AI, and privacy-conscious systems. Currently at BNMIT, shipping real products.
Siddharth P is an Artificial Intelligence & Machine Learning engineering student at BNM Institute of Technology with a strong focus on building practical AI systems. His work spans AI-powered candidate verification, real-time stress detection, offline academic intelligence, anonymous mental wellness platforms, edge AI rider safety systems, automated medical imaging with Vision Transformers, payment data quality, local voice-to-text, privacy tools, and blockchain-enabled environmental impact tracking.
My goal is to build AI systems that solve real problems — in research, education, automation, privacy, and intelligent workflows. I combine AI models, automation tools, full-stack development, local LLMs, and infrastructure thinking to create products that are practical, scalable, and meaningful.
An offline-first Academic Intelligence System with hybrid retrieval, local Ollama generation, and a full study workspace — no cloud, no subscriptions.
NirmiqResearchOS is an offline-first, privacy-conscious academic intelligence system. It features a FastAPI backend with hybrid BM25 + Chroma vector retrieval (RRF reranking), and a custom Next.js study workspace with 10 study modes — from deep research to exam answers and revision notes. Documents (PDF, text, markdown, images) are ingested locally, chunked, and indexed with page-level caching. Generation and embeddings run through Ollama. Zero cloud dependency.
A selection of AI, automation, research, privacy, health, and blockchain systems I've built or am actively building.
Hackathon results and certificates from the past few months — built and shipped within 24–48 hour windows.
Ways I can support AI, automation, and product-building projects.
Open to internships, AI/ML projects, collaborations, research opportunities, freelance automation work, and product-building opportunities.