Orimon.ai is a cutting-edge platform that uses AI to create interactive and human-like chatbots for businesses. These AI chatbots manage customer interactions across various channels including email, chat, and social media. By using deep learning technologies, Orimon.ai ensures swift and efficient responses to customer inquiries, transforming visitor interactions into meaningful conversations. This not only boosts sales and conversions but also reduces operational costs by minimizing the need for large customer service teams.

ragChatbot is a developer-centric framework designed to streamline the creation of Retrieval-Augmented Generation chatbots. It integrates LangChain pipelines with OpenAI or other LLM APIs to process queries against custom document corpora. Users can upload files in various formats (PDF, DOCX, TXT), automatically extract text, and compute embeddings using popular models. The framework supports multiple vector stores such as FAISS, Chroma, and Pinecone for efficient similarity search. It features a conversational memory layer for multi-turn interactions and a modular architecture for customizing prompt templates and retrieval strategies. With a simple CLI or web interface, you can ingest data, configure search parameters, and launch a chat server to answer user questions with contextual relevance and accuracy.

Zipchat is an advanced AI chat support agent designed to facilitate seamless communication between businesses and their customers. Utilizing natural language processing, it provides automated responses to customer inquiries, helping to resolve issues and answer questions in real-time. Moreover, Zipchat can learn from interactions, improve responses over time, and integrate with various business tools to enhance operational efficiency. With an intuitive interface, it is suitable for companies looking to augment their customer service capabilities.

DocGPT is designed to simplify information extraction and Q&A from documents by providing a seamless conversational interface. Users can upload documents in PDF, Word, or PowerPoint formats, which are then processed using text parsers. The content is chunked and embedded with OpenAI's embedding models, stored in a vector database like FAISS or Pinecone. When a user submits a query, DocGPT retrieves the most relevant text chunks via similarity search and leverages ChatGPT to generate accurate, context-aware responses. It features interactive chat, document summarization, customizable prompts for domain-specific needs, and is built on Python with a Streamlit UI for easy deployment and extensibility.