My Projects
Architecting the future of Agentic AI, Autonomous Systems, and Full-Stack Engineering.
Technical Stack
Technical Achievement
AuraDesk bridges the gap between traditional telephony and agentic AI. The V2 refactor evolved the system into a 100% industry-agnostic SaaS engine, featuring sub-second LLM orchestration, ultra-realistic multilingual TTS, and a secure "Supernova" user experience backed by robust cyber-security middleware.
Engineering Challenges & Solutions
Agnostic Multi-Tenant Engine
Re-engineered the core backend into a 100% industry-agnostic SaaS engine. Developed dynamic instruction injection that merges client-specific personalities with universal safety guardrails.
Sub-Second LLM Optimization
Architected a migration to advanced, low-latency LLMs (e.g., Claude Haiku), reducing token costs by 50% and completely eliminating tool narration hallucinations.
Zero-Lag Tool Logic
Implemented rigid asyncio.wait_for "Hard Walls" across external API integrations to prevent dead-air silences and guarantee consistent sub-second response times.
The "Bouncer" Middleware
Engineered a custom IP-reputation system monitoring sensitive paths with tiered automated banning and proxy-aware whitelisting to prevent system lockouts during heavy automated attacks.
High-Fidelity Telephony & TTS
Integrated carrier-level call routing with premium multilingual text-to-speech models, enabling ultra-realistic human intonation and natural pacing without robotic delays.
Supernova UX & Analytics
Refined the client dashboard with a premium dark-mode aesthetic, animated bento-grid displays, and real-time backend integrations for live call-history tracking and ROI scoreboards.
Key Takeaways
Achieved sub-second conversational latency through rigorous LLM optimization and asynchronous API timeouts. Delivered a premium, highly-secure "Supernova" user experience that provides real-time ROI tracking and autonomous operations across any industry.
Technical Stack
Project Goal
To create a digital presence that matches the elite quality of Little Pockets' work, providing a seamless booking and service discovery experience for luxury car owners and commercial fleet managers.
Key Features & Deliverables
Premium Aesthetics & Branding
Designed a high-end, visual-first interface that reflects the luxury and precision of elite vehicle customization.
Service Showcasing
Developed interactive sections for luxury wraps, paint protection film (PPF), ceramic coatings, and commercial graphics.
Performance & SEO
Optimized for lightning-fast load times and localized SEO to dominate the Michigan vehicle customization market.
Mobile-First Experience
Ensured 100% responsiveness for customers browsing exotic car transformations on the go.
Technical Stack
Project Vision
Instagram Pro Tools is a high-performance Chrome Extension (Manifest V3) designed to strip away intrusive UI elements and provide a "Theater Mode" for an optimized Instagram desktop experience. It tackles the challenges of modifying a complex, obfuscated React-based DOM to deliver a cleaner, more immersive user interface.
Engineering Challenges & Solutions
Theater Mode (UI/UX Optimization)
Engineered targeted CSS selectors to identify and modify Instagram's complex React-based modal structures, expanding media containers to 100% width while preserving site integrity.
Persistent State Management
Implemented a robust feature toggle system using chrome.storage.local and chrome.scripting, ensuring user preferences (Theater Mode, Play Button Hider) persist across browser sessions.
The 'Shotgun' CSS Strategy
Developed a resilient CSS injection method to neutralize obfuscated class names and persistent video overlays (Reels, Feed Posts), solving the 'DOM-Whack-A-Mole' challenge.
Sleek Popup Controller
Designed a modern, dark-mode control panel using Vanilla CSS and Asynchronous JavaScript, providing real-time visual feedback via dynamic icon badges and color-coded status indicators.
Tech Stack
Project Vision
The era of manual searching is over. OmniCart is a visual intelligence engine that bridges the physical and digital worlds, transforming your phone into an autonomous economic agent. We are moving from "searching" for products to "commanding" outcomes.
Key Features & Roadmap
Phase 1: The Visual Scout (V1)
"The Shazam for Shopping."
- Visual Search: Snap a photo of any item, and OmniCart's AI identifies it.
- AI-Powered Aggregation: The engine scrapes the global web for the best matches, prices, and alternatives in real-time.
- Frictionless Experience: Built on a secure, cross-platform architecture for a seamless experience on both iOS and Android.
Phase 2: The Agentic Awakening (V2)
Your AI agent takes action.
- Autonomous Execution: Set your price and command your agent to execute the purchase when the conditions are met.
- Predictive Logistics: The agent anticipates your needs, queuing up actions for your approval.
- Negotiation Bots: In the future, AI agents will negotiate prices with sellers on your behalf.
Tech Stack
Project Goal
To engineer a fully autonomous, 24/7 social media marketing agent that moves beyond simple scheduling. The system is designed to intelligently source, create, and publish content using a Hybrid Retrieval-Augmented Generation (RAG) Architecture, ensuring resilience and relevance.
Key Features
Live Intelligence Gathering
Scrapes real-time web data to discover breaking industry news and relevant topics, ensuring content is always timely.
Contextual Content Synthesis
Uses Google's Gemini to synthesize long-form articles and reports into engaging, platform-specific threaded conversations.
Generative Visuals
Autonomously prompts DALL-E 3 to create context-aware memes and promotional imagery that align with the generated text.
Self-Healing Architecture
Features a robust try-except-cache loop. If an API rate limit or connection drop occurs, the system caches the content and retries, ensuring zero data loss.
Outcome
The agent successfully runs continuously on a Linux server, autonomously generating and posting high-quality, relevant content to social media platforms like Twitter and LinkedIn. Its self-healing capabilities have proven effective in handling network and API interruptions, resulting in a truly hands-off marketing automation solution.
Tech Stack
Project Goal
To develop a fast-paced, responsive web game, demonstrating proficiency in front-end development, game logic implementation, and real-time database integration for a global leaderboard.
Key Features
Real-Time Rendering Loop
Utilized the HTML5 Canvas API and `requestAnimationFrame` for a smooth, high-performance game loop, independent of React's render cycle.
Advanced State Management
Leveraged React Hooks (`useState`, `useRef`, `useCallback`) for efficient state management and to prevent re-renders during active gameplay.
Global Leaderboard
Implemented a global leaderboard using Firestore, including secure data submission and real-time score updates.
Responsive Controls
Created a seamless user experience with intuitive controls across both desktop (keyboard) and mobile (touch) devices.
Future Expansion
This project serves as a foundation for more complex web-based games. Future plans include adding power-ups, more enemy types, and progressively difficult levels to enhance gameplay depth.
Tech Stack
Project Goal
To develop a sophisticated algorithmic trading bot that executes trades based on custom strategies written in Pine Script. This bot is designed to automate trading decisions and capitalize on market opportunities 24/7.
Key Features
Custom Strategy Development
Leverages Pine Script to create and implement complex, custom-tailored trading strategies from the ground up.
TradingView Integration
Seamlessly integrates with TradingView for real-time charting, analysis, and alert-based trade execution.
Automated Execution
The bot autonomously executes trades when market conditions meet predefined criteria in the Pine Script strategies, operating 24/7.
Robust Backtesting
Utilizes Backtesting.py and Python to rigorously test and optimize trading strategies against historical data, ensuring viability and performance before deployment.
Outcome
The resulting system provides a powerful framework for quantitative trading, enabling rapid prototyping and validation of complex strategies. It successfully automates the entire workflow from idea to execution.