AI Chatbot Development Projects in KarachiAI Chatbot Development Projects in Karachi
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Cover image for PRESTORATIVE™ (Pacific Plant Nutrients) I designed
PRESTORATIVE™ (Pacific Plant Nutrients) I designed this website for an agricultural biostimulant brand that needed to earn trust from two very different audiences: growers who want application rates, and evaluators who want evidence. The goal was to make a technical product feel credible without leaning on bold marketing claims. The hero states the idea plainly, "Feed the soil before it asks," and immediately splits visitors into two paths: "I grow, show me rates" and "I evaluate, show me the evidence." Each audience reaches what it needs in one click. I used deep forest green, warm cream and an amber accent, pairing an editorial serif for headlines with monospace type for data. The result feels grounded and scientific rather than salesy. Instead of vague benefits, the page is built on proof. It includes a crop-by-crop rate engine, an AI technical assistant that answers from product documentation, an evidence library with clear grading tiers, and a section that openly addresses the toughest objection buyers raise. Every section moves the visitor from understanding to confidence, and ends with one clear action: design a trial.
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Cover image for Smart WhatsApp AI Chatbot Automation Designed
Smart WhatsApp AI Chatbot Automation Designed and developed a fully automated WhatsApp AI chatbot system that transforms how businesses handle customer communication and operations. This solution connects WhatsApp with core business workflows, enabling real-time responses, intelligent appointment scheduling, seamless order processing, and automated follow-ups — all without manual intervention. The system leverages n8n automation workflows, OpenAI API, webhooks, and custom API integrations to create a scalable and efficient backend. Customer inquiries are intelligently understood and routed, allowing businesses to capture customer information, manage support queries, and process transactions directly within WhatsApp. The focus of this project was to build a clean, reliable, and production-ready automation system that reduces response time, improves customer experience, and streamlines internal operations. The architecture is modular, making it easy to extend with additional integrations and business logic as needed. This project reflects a modern AI automation approach, combining conversational AI with workflow automation to create a powerful, real-world business solution.
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Cover image for Stop playing email tennis. Here
Stop playing email tennis. Here is how I built an autonomous 24/7 AI Booking Agent 🗓️🤖 Most service businesses and creative agencies lose high-value revenue simply because they take hours to manually qualify and respond to inbound discovery inquiries. I engineered this custom event-driven automated pipeline to eliminate manual scheduling overhead completely. How the architecture handles inbound traffic smoothly: 1️⃣ A user interacts with a customer-facing Typebot chat interface. 2️⃣ The raw conversation data passes instantly via webhook to n8n logic routers. 3️⃣ An OpenAI API engine scores the intent data as a "Hot" or "Cold" lead. 4️⃣ Hot leads instantly get auto-routed to a pre-filled Calendly checkout link. 5️⃣ Zero manual data entry—everything syncs smoothly to Google Sheets and fires confirmation updates via Gmail. 🛠️ Tech Stack: Typebot • n8n • OpenAI • Calendly • Google Sheets • Gmail 👉 Need this engine built to scale your business operations? Check out the full technical Case Study breakdown and see my live build notes directly on my profile!
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Cover image for AI Customer Support Agent with
AI Customer Support Agent with Knowledge Base Businesses lose valuable time answering repetitive customer questions. I built an AI-powered customer support agent that provides instant, accurate responses by searching company documentation instead of relying solely on a language model. The assistant uses Retrieval-Augmented Generation (RAG) to retrieve relevant information from PDFs, FAQs, user manuals, and internal knowledge bases before generating responses. Every answer includes source citations, allowing users to verify the information with confidence. Key Features ✅ AI-powered customer support ✅ Knowledge Base & PDF ingestion ✅ RAG-based semantic search ✅ Conversation memory ✅ Source citations for every response ✅ Enterprise admin dashboard ✅ Responsive web interface for desktop and mobile Tech Stack Python Django OpenAI LangGraph PostgreSQL RAG (Retrieval-Augmented Generation) Business Impact • Reduced repetitive support requests by providing instant AI responses • Improved customer experience with 24/7 availability • Increased trust through citation-backed answers • Centralized company knowledge into a searchable AI assistant • Scalable architecture for enterprise support teams Building AI applications isn't just about integrating an LLM—it's about designing reliable systems that deliver accurate, explainable, and production-ready results. If you're looking to build an AI-powered customer support platform, internal knowledge assistant, or enterprise RAG application, I'd be happy to discuss your project. #AI #OpenAI #Python #Django #LangGraph #RAG #ArtificialIntelligence #CustomerSupport #KnowledgeBase #SaaS #MachineLearning #EnterpriseAI #Automation #SoftwareDevelopment #Contra #Freelancer
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