Helping businesses scale through intelligent workflows, custom AI agents, and seamless integrations. I specialize in turning complex manual processes into efficient, automated systems.

• 🔭 I’m currently working on: UreatorFlow (AI operating studio for solo creators) and NBGC (Photos to UGC ads).
• 🌱 I’m currently learning: Advanced Multi-Agent Orchestration and scaling SaaS with Lovable & n8n.
• 👯 I’m looking to collaborate on: Open-source AI automation workflows and innovative SaaS projects.
• 💬 Ask me about: n8n automation, AI Agents, Supabase integration, and building a SaaS portfolio.
• 📫 How to reach me: LinkedIn , Mail or WhatsApp
• ⚡ Fun fact: I don't just write code! I code the vibe. ✨

Category	Tools & Technologies
Automation & No-Code
AI & LLM Models
AI Dev & Databases
Web Dev & Frameworks
Editors & OS Tools
Specialized Tools

An AI-powered operating studio designed specifically for solo creators to automate their content ecosystem.

• Core Tech:
• Key Features: Automates content planning, scheduling, and distribution workflows.
• Status: Live Demo

A high-efficiency automation pipeline that transforms raw product photos into high-converting UGC ads using AI.

• Core Tech:

graph LR
  A[Raw Photo] --> B[Gemini Vision AI]
  B --> C[Ad Copy & Design]
  C --> D[UGC Asset Ready]
  style B fill:#8E75B2,color:#fff

• Impact: Automated asset creation for marketing agencies.

• Status: Live Demo

An advanced AI Agent system that understands user intent and retrieves contextually relevant information from custom databases using Vector Search.

• Core Tech:

graph TD
  User((User Query)) --> Hook[n8n Webhook]
  Hook --> Embed[Embedding]
  Embed --> Search{Vector Search}
  Search -- Query --> PDB[(Pinecone/MongoDB)]
  PDB -- Context --> AI[AI Model]
  AI --> Result[Synthesized Answer]
  Result --> Response[Response]

  style Search fill:#f9f,stroke:#333
  style PDB fill:#27272e,stroke:#fff,color:#fff

• Key Features: Intent recognition, dynamic context retrieval, and low-latency AI responses.

• Use Case: Custom AI chatbots for businesses that need to talk to their own data.

An autonomous, multi-modal AI Sales Agent designed for Facebook Messenger. This agent handles the entire sales lifecycle—from product inquiries (text, voice, image) to inventory checking, fraud detection, and order placement—while maintaining a seamless human handoff protocol.

• Core Tech:

graph TD
  User((User Input)) --> Webhook[n8n Webhook]
  Webhook --> Router{Input Type?}
  
  Router -->|Image| Vision[Gemini Vision Analysis]
  Router -->|Voice| Audio[OpenAI Whisper Transcribe]
  Router -->|Text| Token[Token & Transfer Check]
  
  Vision --> Agent
  Audio --> Agent
  Token --> Agent
  
  Agent["🤖 AI Sales Agent (RAG)"]
  
  subgraph Tools [Agent Tools & Memory]
    direction TB
    Agent <--> GSheets[("Google Sheets: Stock/Orders")]
    Agent <--> Vector[Pinecone: FAQ/RAG]
    Agent <--> History[BD Courier API: Fraud Check]
    Agent <--> Handover[Supabase: Human Handoff]
    Agent <--> Memory[Postgres Chat Memory]
  end
  
  Agent -->|Response| Messenger[FB Messenger Reply]
  
  style Agent fill:#FF6D5A,color:#fff,stroke:#fff
  style Tools fill:#2D3B45,color:#fff,stroke:#fff

• 👁️ Multi-Modal Intelligence: - Uses Gemini Vision to identify products directly from customer photos.

  • Uses OpenAI Whisper to transcribe and understand voice notes in real-time.

• 📦 Smart Inventory System: - Real-time bi-directional sync with Google Sheets.

  • Checks stock before confirming orders and auto-updates inventory after sales.

• 🛡️ Fraud Detection: - Integrated with BD Courier API to analyze customer phone numbers and delivery history (Success/Return ratio) before accepting COD orders.

• 🧠 RAG & Long-Term Memory: - Uses Pinecone Vector DB for retrieving FAQs/Policies.

  • Maintains conversation context using Postgres memory.

• 🤝 Human Handoff Protocol: - Intelligent intent detection triggers a seamless transfer to a human agent via Supabase when complex support is needed.

• 🔗 Status: Source Code