A selection of AI systems I have designed and built, ranging from production deployments serving real users to focused engineering explorations. Ordered by technical depth.
01
LLM Guardrails Gateway
2026
Middleware for LLM input/output safety, built from scratch as a decorator API that drops into any pipeline regardless of provider.
Proven across both Groq and OpenAI providers. YAML-driven policy engine, full audit logging, and a self-eval harness with documented, honest known limitations rather than inflated claims.
FastAPIGroqOpenAIPolicy EngineAudit Logging
Request flow through the gateway, with blocked requests short circuited before reaching the provider
02
Enclave.AI
2025
A privacy-first, multi-agent enterprise AI platform built for Indian BFSI companies navigating RBI and DPDP compliance.
Built from scratch on Ollama and Qdrant, with BAAI/bge-base-en-v1.5 embeddings. LangGraph orchestrates a multi-agent system across retrieval, reasoning, and compliance agents. FastAPI backend, Next.js frontend.
A production-grade voice AI agent that takes real phone calls for a CA firm, listening and responding in real time across Hinglish, Telugu, and English.
Sarvam Saarika for speech-to-text with automatic language detection, Groq's Llama 3.3 70B for responses, Sarvam Bulbul for text-to-speech. Full 8-phase system design documented end to end. Currently blocked on Exotel's bidirectional audio playback pending KYC/TRAI verification on the trial account.
Real-time voice pipeline handling speech to text, LLM response generation, and text to speech across Hinglish, Telugu, and English
05
LLM Eval Pipeline
2025
An automated evaluation pipeline built to understand evals deeply enough to defend design decisions in interviews, not just run a benchmark.
Golden dataset design, heuristic evaluators alongside LLM-as-judge scoring, an async FastAPI pipeline, GitHub Actions CI/CD, and a Streamlit dashboard for reviewing results.
FastAPILLM-as-JudgeGitHub ActionsStreamlit
Golden dataset flowing through heuristic and LLM-as-judge evaluators into a live results dashboard, triggered automatically on every run
06
ArigatoAI
2025 to Present
A production RAG chatbot handling tax and compliance queries for a real CA firm. Retrieves from 2,400+ indexed vectors and responds in under 2 seconds, running live for actual clients daily.
Pinecone for vector storage, OpenAI embeddings, Groq's Llama 3.3 70B for generation. FastAPI backend, Next.js frontend, with an embeddable website widget and an admin dashboard, deployed on Render and Vercel.
An AI-powered visa assistant for international students navigating F1, OPT, CPT, and H1B questions. Features real-time model switching between Llama 3.3 70B, GPT-4o mini, and Gemini 1.5 Flash, so you can compare answers across providers instantly.
Built a unified LLM client in FastAPI that abstracts Groq, OpenAI, and Google APIs behind a single interface. Persistent chat history, markdown rendering, and a clean sidebar, all deployed on Render and Vercel.
An open-source AI companion for any website. Drop a single HTML script tag and an animated character (Samurai, Fighter, or Shinobi) appears, walking across the screen and ready to chat.
Built with pure vanilla JavaScript and zero dependencies. It supports multiple AI providers including Groq (Llama 3.3 70B), OpenAI, Anthropic, and Gemini. Fully configurable via data attributes with a strict focus on local privacy (API keys stay in the browser).