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💯 💯 💯 AI Customer Support Chatbot
Built an AI-powered customer support chatbot for a business website to help answer common customer questions, collect lead information, and reduce manual support work.
The main goal of this project was to create a smart assistant that could respond to visitors in real time, guide them through basic questions, and forward qualified leads to the business team. I developed the chatbot flow, connected the AI model, created backend logic for message handling, and integrated the widget into the website.
The system was designed to understand user questions, provide helpful answers based on predefined business information, and collect important details such as name, email, phone number, service interest, and message intent. I also added fallback handling so the chatbot could redirect complex questions to a human team member.
What makes this work special is that it was not just a simple chat widget. It was designed as a business automation tool to improve response speed, capture leads, and support customers even outside normal working hours.
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Echo is a multi-tenant SaaS for AI customer support with realtime chat, an AI voice agent, and AI automation. I was the primary developer on the full build, frontend, backend, and the AI layer. The AI is the core. It runs OpenAI, Claude, Gemini, and Grok through one multi-model setup, so a client can switch providers without a rewrite. A RAG pipeline connected to a vector database grounds every answer in the client's own content, so the chatbot never returns generic output. VAPI powers the voice agent, so customers can speak to support on a live call. Each tenant gets its own AI agent built on its own documents. The stack is Next.js 15 and React 19 inside a Turborepo monorepo, with separate apps for the dashboard, the embeddable chat widget, and backend services. Realtime chat runs on Convex. Clerk handles auth. API keys are encrypted per tenant through AWS Secrets Manager, so no two clients share credentials or data. Launch day held 60 live conversations at once with zero dropped sessions. What the client gets: an AI chatbot and voice agent that answer from their own content, work across multiple LLM providers, and stay isolated and secure per tenant.:
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🌲 Restore Seferihisar - is a restoration platform to make environmental loss visible and drive real environmental action. I live in Seferihisar, on Turkey's Aegean coast, where more than 75,000 hectares of forest cover have been lost across the region in a decade — I've seen it in my own backyard.
Workflow: Wonder Chat (3 pages) → MCP → Cursor (Next.js) → scroll animations + Lottie polish.
Wonder Features: Built the dashboard, community hub, and transparency ledger using Wonder Chat. Connected Wonder directly to Cursor via MCP to pull visual tokens straight from the canvas to code.
Design in Wonder. Build in Cursor. Connected by MCP. Because I live here, and every single square meter matters.
Frontend DevelopmentWeb DesignWeb DevelopmentCursorNext.jsWonderwonderchallengewebdesignwebdeveloper
A wonderful project that draws attention to environmental issues. People need to become more aware of this issue. I commend you for this project that highlights environmental issues. Here’s hoping for a greener world.
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