RouteEye
BIAL · Production deploymentReal-time fleet infrastructure running in production at Bangalore International Airport.
High-frequency platform processing vehicle telemetry every ~5 seconds, streamed live to airport operations.
Building production agents, real-time platforms and distributed systems — from 0→1 through production.
Production systems and experiments — what they do, who uses them, and how they're built.
A shell fixer that removes the trigger key between a mistake and the fix.
Hooks Enter in zsh and bash: safe typos resolve locally, natural-language commands route to an optional AI provider, and anything risky waits for confirmation. Works with existing Codex, Claude Code, or OpenCode logins—no extra API key required.
Real-time fleet infrastructure running in production at Bangalore International Airport.
High-frequency platform processing vehicle telemetry every ~5 seconds, streamed live to airport operations.
Production AI agents deployed for real businesses.
No-code platform to create, deploy, and manage AI agents on any website — powering 10+ live businesses across WooCommerce, Shopify, and WordPress.
Interfaces where AI returns interactive software instead of only text.
An agent that answers with live React components — a form when fields are missing, a chart when the trend matters — streamed over AG-UI with human-approved writes.
Repository-local Codex skills that collect evidence from GitHub, generate recurring progress summaries, answer questions across saved reports, and export the results as polished Excel workbooks.
Multi-agent personal assistant built with LangGraph & OpenRouter. Supervisor agent routes to specialized sub-agents for task management, Google Calendar integration, daily planning, and personal data storage. Deployed on AWS ECS Fargate with React + Vite frontend on S3/CloudFront.
Drink-spiking prevention platform combining portable spectroscopy hardware with a real-time mobile safety app. SOS alerts, live location sharing, and sub-3-second scan results.
Multimodal RAG platform on Azure. Documents uploaded to Blob Storage → text & images extracted → embedded via text-embedding-3-small → indexed in Azure AI Search → GPT-4.1 powered chat with contextual recall. Retrieval surfaces relevant text chunks + images together.
End-to-end agentic commerce on the Universal Commerce Protocol: an AI shopping agent (Google ADK + Gemini), a FastAPI merchant reference implementation, and a Next.js storefront. The agent discovers the merchant from a single URL, links identity via OAuth, and completes real checkouts — all three services deployed and live.
Open-source Go library for ORM-level audit logging with GORM. Tracks create/update/delete events with minimal configuration overhead.
Config-driven AI tutoring agent built with Google ADK and Gemini — YAML-defined agent, markdown prompts, dynamic tool loading, calculator and Google Search tools. Companion repo to the AI Agent System blog series.
Local execution framework for AWS Bedrock agents — run and test Bedrock AI agents in a local development environment with multiple interface modes.
Image search powered by Google Gemini multimodal capabilities. Enables semantic search across images using AI embeddings and vector similarity.
The shell fixer with no trigger key — typo fixing + optional AI natural-language commands for zsh/bash. Just type what you mean and press Enter. macOS + Linux, MIT.
Agentic Dynamic UI — an AI agent that answers with live, interactive React components (forms, tables, charts, confirm cards) instead of plain text, streamed over AG-UI. CRM reference implementation.
AI shopping agent (Google ADK + Gemini) that discovers, browses, links identity, and completes checkout on any UCP-enabled merchant — entirely through conversation.
Reference implementation of the Universal Commerce Protocol (UCP) — a FastAPI merchant layer that lets AI agents discover, authenticate, and transact with online stores.
Ideas I'm actively developing — on AI, interfaces, and where software is going.
I like building systems where software meets the messy real world. That has taken me from real-time infrastructure and IoT systems to production AI agents and agentic interfaces.
About me