2
2
India
2+ years of experience
I am a dedicated Student at JNTU Kakinada with 2 years of experience in building and innovating within the AI space. Based in India, I am passionate about technical development and leveraging cutting-edge technology to create impactful AI solutions. I'm always looking for opportunities to collaborate on projects that push the boundaries of whatβs possible in tech

Navigating the recently overhauled Indian criminal justice system, which introduces the Bharatiya Nyaya Sanhita (BNS), Bharatiya Nagarik Suraksha Sanhita (BNSS), and Bharatiya Sakshya Adhiniyam (BSA), is a massive challenge for both legal professionals and everyday citizens. NyayaLLM solves this by providing a highly accurate, domain-specific AI assistant trained exclusively on these new legal frameworks. We leveraged the immense compute power of AMD MI300X instances to fine-tune a Llama 3.1 model, ensuring rapid iteration and high throughput during the training phase. By utilizing ROCm and Hugging Face libraries, we adapted the base model to understand complex legal jargon, procedural nuances, and the specific relationships between the old IPC/CrPC sections and the newly implemented BNS/BNSS codes. The resulting application allows users to query specific legal scenarios, understand compliance requirements, and draft preliminary legal summaries with significantly reduced hallucinations compared to standard, general-purpose models. Our ultimate goal with NyayaLLM is to democratize legal knowledge, increase productivity for law firms dealing with the transition, and ensure that the complexities of the new Indian criminal laws do not become a barrier to justice.
10 May 2026

MedGuardAI is a real-time AI assistant designed to reduce clinical errors and enhance decision-making in healthcare. The system leverages large language models (LLMs) to analyze patient records, prescriptions, and medical histories to detect misdiagnoses, medication conflicts, dosage anomalies, and documentation issues. It enables patients to securely share their medical data with doctors via token-based access, ensuring data privacy and control. Built using Groq API, LLaMA, Firebase, and Supabase, MedGuardAI functions in low-resource settings without requiring expensive infrastructure. The assistant provides explainable outputs to build trust and transparency, making it a practical tool for improving patient safety and healthcare outcomes.
8 Jul 2025