I build backend systems and AI tools under real-world constraints: limited hardware, noisy inputs, and users who value speed and clarity over complexity.
My work focuses on making language models and automation useful—especially on lightweight infrastructure and edge devices. I care about efficiency and robustness, not just benchmarks.
I value clean abstractions, measurable trade-offs, and software that survives contact with reality.
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Voice-activated assistant for Raspberry Pi: music, task management, and game launching with modular features. Built for tight latency and power constraints.
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Adaptive language-learning bot focused on retention and feedback loops.
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Encrypted note-taking system balancing usability and privacy.
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AI-powered legal assistant for Indian law (research, document analysis, drafting). Plus production systems and experiments.
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STEMist Education — Chapter Lead & Technical Lead. Founding the STEMist chapter at Boys' High School, Prayagraj; building a zero gate-keeping, builder-focused STEM club with hands-on workshops and demo days.
Bits&Bytes — Founding Member & Technical Lead. Shaping vision and running hackathons, coding workshops, and tech events for young developers; managing website, comms, and event systems.
Previously Jr. Research Engineer at jhana (Nov 2025–Jan 2026): AI-powered legal tech—WhatsApp conversational flows with Gemini voice transcription, multimodal legal consultation analysis, natural-language command parsing for document editing and version control, concurrent processing for real-time message streams.
Languages: Python, TypeScript, Dart, Bash, SQL
Backend & APIs: FastAPI, Next.js, REST APIs, LangChain, Discord.py, Telegram Bot API
AI / ML: LLMs, OpenAI API, Groq, fine-tuning, NLP, Docker, LLMOps
Hardware & edge: Raspberry Pi, ESP32, Arduino
Cloud & data: AWS, EC2, Azure, SQLite, Pinecone, Vercel
Tools: Linux, Git, GitHub, CI/CD basics
- Efficient inference and model compression (quantization, LoRA/QLoRA, lightweight fine-tuning)
- Retrieval-augmented generation for structured and semi-structured data
- Edge and on-device AI where latency, power, and privacy matter
- Systems that stay useful under pressure—robust when sensors and inputs are noisy



