Rashid Khabeer
Full-Stack Agentic AI Dev | n8n • Make • GHL Automation
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Developed a comprehensive, end-to-end automation engine using n8n to replace slow, error-prone manual profit margin calculations with real-time, data-driven visibility. The system synchronizes order data across ShipStation, BigCommerce, and major marketplaces like Amazon and Walmart, integrating complex logic for item-level costs, multi-currency conversions (via Frankfurter API), and customer-specific discounts within Airtable. This automation reduced processing time to seconds per order and eliminated manual entry errors. Key strategic features include a low-margin detection system with an integrated team review workflow, automated management reporting, and a robust architecture handling deduplication and missing data fallbacks. The solution provides immediate, reliable profitability insights for pricing and operational decision-making.
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The MCAT King of the Curve project is a sophisticated RAG-based (Retrieval-Augmented Generation) backend designed to revolutionize how medical students interact with vast amounts of unstructured study data. Built using Python and OpenAI, the system addresses the challenge of static, overwhelming notes by allowing users to upload diverse file formats—including PDFs, Excel, and images—and transform them into a searchable, interactive knowledge base. By utilizing ChromaDB for vector embeddings and semantic search, the platform provides highly accurate, source-grounded answers in under three seconds, effectively eliminating AI hallucinations. Beyond simple Q&A, the backend features a specialized "Classroom Mode" that auto-generates MCAT-style questions across varying difficulty levels, offering a gamified, scalable, and secure environment that prioritizes data isolation and high-performance reliability for high-stakes exam preparation.
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Built JuvaBun, an AI-powered sales chatbot for a hair extensions e-commerce site, designed to automate customer conversations and drive conversions. The bot answers product questions, asks guided follow-ups, and recommends products based on hair type, budget, and user intent. Integrated rich product content including images, videos, reviews, and comparisons to reduce buyer hesitation. Implemented checkout link sharing, abandoned-chat follow-ups, and upsell flows for higher-value bundles. Designed the system with intent detection, fallback handling, and conversation recovery to avoid dead ends, improving engagement while reducing manual sales effort.
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I optimized this GoHighLevel (GHL) CRM to transform lead management into a high-conversion sales engine. I built a custom multi-stage pipeline from MQL to Scope Approved to ensure zero lead leakage.
Key Deliverables:
1- Pipeline Architecture: Structured stages for clear sales visibility.
2- Lead Tracking: Integrated source tracking (Organic/Forms) to measure ROI.
3- Revenue Monitoring: Real-time dashboard showing $4,000+ individual deal values.
4- Efficiency: Streamlined 170+ opportunities for faster follow-ups and higher closing rates.
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