PropLlama.ai is a real estate platform designed to transform the daunting and intricate task of navigating the property landscape into a seamless and enjoyable experience. Our platform features an intelligent chatbot that understands, remembers, and responds to your queries like a trusted friend, making it feel like you are having a meaningful conversation with a property confidant rather than just another chatbot. Additionally, our platform offers 24/7 chat support with a team of seasoned experts, personalized property searches, insightful decision-making support, comprehensive assistance throughout the property acquisition process, and meticulous legal compliance support. This includes everything from document verification to crafting customized lease agreements. With PropLlama.ai, you get convenience, speed, and accuracy at your fingertips, making it your ultimate real estate companion and doubt resolver. Say goodbye to data overload, questionable broker integrity, and the stress of legalities. PropLlama is here to guide you through it all. The core of PropLlama.ai is powered by the Llama-13b-alternative chat model(tested with Llama-70b too) and Clarifai. It enables the chatbot to understand the context of a conversation, remember previous interactions, and generate human-like responses. It can also process text data, such as property descriptions, legal documents, and news articles, to extract relevant information and provide personalized recommendations to users. Langchain Agents and LLMs- Various tools which were built using Llama and Clarifai for variety of class of queries were intergrated using Langchain agents. LangChain is a framework designed to simplify the creation of applications using large language models (LLMs) In summary, PropllAma.ai leverages advanced technologies, such as the Llama-13b-alternative chat model, Clarifai platform, Llama-70b model for testing, and Langchain agents and LLMs,

An AI sports trainer integrates advanced AI technologies, including large language models (LLMs), retrieval-augmented generation (RAG), convolutional neural networks (CNNs), and rule-based models, to deliver comprehensive analysis of athletic techniques. By tracking specific motion details—such as hand movement, hip rotation, leg positioning, and overall body alignment—it identifies technical inconsistencies and areas for improvement. CNNs enable in-depth visual analysis, while LLMs and RAG retrieve tailored guidance from vast training data, creating a system that offers highly personalized, sport-specific feedback. This AI-driven trainer enhances skill development and helps athletes reach peak performance with precision and efficiency.