About
An AI Engineer Who Builds the Whole App
Give me a problem and I'll take it all the way to a product people can use. 7 of them are live on this site.
I'm Taaran, an AI Engineer in Jaipur, India. I started in data science, moved into machine learning and deep learning on production systems, and now build LLM products: retrieval systems that cite their sources and agents that decide which tool to use.
The problems I enjoy most are the ones where a model has to earn trust: an answer that needs a source, a prediction someone will act on, an alert that can't cry wolf. That's why I build the backend and the interface myself, so I can see how the AI behaves for the person actually using it.
I make trade-offs deliberately. A smaller model if it's fast enough, files on disk when one server will do, a rule-based fallback when the AI is slow. Each case study shows those choices, the numbers behind them and what I'd change next time.
LLM & RAG Engineering
RAG pipelines that cite the exact page and line, LangGraph agents that pick which tool to call, and one app that runs on 8 LLM providers.
Machine & Deep Learning
ML and deep learning anomaly detection on production logs, neural networks that learn to drive, calibrated churn models, and a workbench comparing 68 algorithms.
Full-Stack Engineering
FastAPI backends, Next.js and TypeScript front ends, Docker deploys, and the rate limits and quotas that let strangers use a free demo safely.
Numbers Over Adjectives
Held-out evaluation, calibration error, and latency and token cost per request. The case studies also cover what failed the first time.
7
AI products live with demos
3
Companies shipped for
10+
Industries served
2
Research papers published