Projects

Production-ready systems built with purpose and care.

AI Projects

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MCP Schedule Meeting Server

Active Development

A Model Context Protocol (MCP) server that integrates Google Calendar, Notion, and Slack to enable cross-tool orchestration. Reduces context switching and saves users 1–2 hours weekly.

PythonFastAPI
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Agent Workflow Builder

Shipped

A visual tool for designing and deploying agentic workflows. Enables users to orchestrate multi-step AI agent pipelines without writing complex code.

TypeScriptReactNext.jsTailwind CSS
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Terminal Coding Agent

Completed

A terminal-based AI coding assistant that helps developers write, debug, and refactor code directly from the command line. Designed for efficiency and minimal context switching.

BashTypeScriptGemini API
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AI Customer Support Voice Agent

Completed

An AI-powered customer support system built for Aven, featuring real-time chat and voice Q&A capabilities. Reduced customer support workload by 25%+ through intelligent query handling.

Next.jsTypeScriptPineconeVercel
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Eid Community Platform

Active Development

A full-stack community platform built for the Muslim community, featuring event coordination, community engagement tools, and an AI-powered Islamic Q&A feature using RAG to provide trusted, cited answers.

ReactNode.jsExpress.jsPostgreSQLRedisDocker

ML Projects

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Personalized X Recommendation Algorithm

Shipped

A personalized reimplementation of the X recommendation algorithm exposing the full ranking pipeline as a tunable, inspectable engine. Built a resilient ML-adjacent LLM pipeline for ~2,000 sequential Gemini API calls using exponential-backoff retries, 1.5s rate-limit delays, and O(1) duplicate detection — delivering zero data corruption across 500 persona generations and 4 content types.

TypeScriptNext.jsGemini APIMachine Learning
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Autonomous ML Agent

Shipped

An autonomous machine learning agent that ingests tabular datasets, automatically cleans and preprocesses data, trains models, and optimizes them for target metrics like accuracy, precision, or recall. The entire pipeline is orchestrated by LLMs that generate and modify code, select algorithms, and iteratively refine the pipeline until the best-performing model is achieved.

PythonLLMsScikit-learnPandas