This project develops an autonomous AI concierge system designed for luxury hotels and tourism operators around the V&A Waterfront and Atlantic Seaboard in Cape Town. The system uses multi-agent orchestration to manage bookings, personalize travel itineraries, recommend local experiences, and handle multilingual interactions, delivering intelligent, real-time guest engagement while optimizing operational efficiency.

Key Highlights :-

• Tools & Technologies Used: LLMs (GPT-class models), LangChain-style orchestration, RAG pipeline, Vector Database (Pinecone/FAISS), FastAPI, Python, Azure/AWS Cloud, Speech-to-Text APIs, Docker, Kubernetes.
• Multi-agent architecture for bookings, recommendations, and customer support
• RAG-powered contextual travel intelligence using local tourism data
• Real-time multilingual voice-enabled interaction system
• Scalable cloud-native deployment for hospitality enterprise use

This project builds an Agentic AI system designed to support renewable energy providers across the Western Cape. The platform analyzes solar and wind generation data, predicts demand fluctuations, automates reporting, and recommends grid optimization strategies. It combines real-time analytics with autonomous decision agents to improve energy efficiency and operational sustainability in Cape Town’s green energy ecosystem.

Key Highlights :-

• Tools & Technologies Used: Python, TensorFlow/PyTorch, LLM APIs, RAG Architecture, Time-Series Forecasting Models, Apache Kafka, PostgreSQL, Kubernetes, Azure/AWS, MLflow.
• Autonomous decision-making agents for grid balancing
• LLM-powered regulatory and reporting automation
• Predictive demand forecasting with time-series ML
• Secure enterprise-grade deployment with monitoring dashboards

This project creates a Generative AI-powered document intelligence system tailored for real estate and property management companies in Cape Town’s growing PropTech sector. The solution automates lease agreement analysis, compliance verification, tenant communication, and property insights using RAG and multi-agent workflows, significantly reducing manual legal review time and improving decision accuracy.

Key Highlights :-

• Tools & Technologies Used: LLM APIs, LangGraph/Multi-Agent Framework, Vector Database, OCR (Tesseract), Python, FastAPI, PostgreSQL, Azure Blob Storage, Docker, CI/CD pipelines.
• Automated lease analysis with semantic document parsing
• Multi-agent compliance validation workflow
• Secure tenant-based data isolation architecture
• End-to-end enterprise deployment with audit logging