Ruslan Sheikh
AI Engineer | LLM Agents, Automation & RAG Solutions
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Ruslan is ready for their next project!
AI-Powered Customer Support & Information Assistant
I designed and developed an AI-powered conversational assistant that automated information retrieval and customer enquiries for an online marketplace.
The assistant connected users with structured listing and account data through a conversational interface, allowing information to be retrieved without manually navigating multiple parts of the platform.
I built the supporting backend using Node.js, Express.js, MongoDB and REST APIs, integrating application data with automated enquiry workflows and the AI assistant.
I owned the project across the full development lifecycle, including system architecture, backend development, database design, API integration, testing, debugging, deployment and iterative product improvement.
The project demonstrated how AI could be integrated into an existing digital product to make business information more accessible while reducing repetitive enquiry workflows.
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Strategy Consultant Chatbot
I engineered an LLM-powered strategic intelligence agent designed to search, synthesize and deliver insights from complex business information.
I worked on the agent's Generative AI workflows, prompt engineering, contextual reasoning and conversational AI capabilities, helping transform large volumes of information into source-linked, decision-ready responses for strategic use cases.
The system was designed to handle complex, multi-dimensional questions while providing transparent, attributable insights.
This project gave me hands-on experience developing an enterprise AI agent around a real business use case from LLM workflow and prompt design to contextual reasoning and executive-facing delivery.
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AI-Powered Retail Operations & Management Platform
I designed and developed a full-stack retail operations platform that centralized the day-to-day processes of a real operating business into one connected system.
The platform brought together POS and sales processing, inventory and shelf management, stock transfers, customer management, promotions, loyalty rewards, employee shifts and alerts, online orders, analytics, and reporting within a single web application.
I built the solution end-to-end — translating real business requirements into features, designing the system architecture and database, developing the frontend and backend, implementing business logic and APIs, and handling testing and deployment.
I also incorporated AI-assisted capabilities and automation into the wider platform to reduce repetitive operational work, surface useful business information, and support faster decision-making.
The result replaced fragmented workflows with a centralized digital system, giving the business better visibility over sales, inventory, employees, customers, and day-to-day operations, while creating the technical foundation for its e-commerce operations.
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AI-Powered Insurance Fraud Detection Platform
I designed and built an end-to-end AI-powered platform for detecting and investigating suspicious health insurance claims.
The system combines machine learning, XGBoost, anomaly detection and behavioral analytics with a multi-stage RAG and document intelligence pipeline for AI-assisted claims investigation. I also developed an interactive React + D3.js dashboard for exploring fraud networks, geographic patterns, anomalies and explainable model outputs.
This project took me through the complete AI product lifecycle from data analysis and feature engineering to LLM orchestration, frontend development and interactive data visualization.
Built with: Machine Learning · XGBoost · RAG · LLMs · Document Intelligence · React · D3.js · Explainable AI
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