Granite Retrieval Agent provides developers with a flexible platform to build retrieval-augmented generative AI agents that combine semantic search and large language models. Users can ingest documents from diverse sources, create vector embeddings, and configure Azure Cognitive Search indexes or alternative vector stores. When a query arrives, the agent retrieves the most relevant passages, constructs context windows, and calls LLM APIs for precise answers or summaries. It supports memory management, chain-of-thought orchestration, and custom plugins for pre- and post-processing. Deployable with Docker or directly via Python, Granite Retrieval Agent accelerates the creation of knowledge-driven chatbots, enterprise assistants, and Q&A systems with reduced hallucinations and enhanced factual accuracy.

CEBot employs a large language model (LLM) to deliver informative answers and insights to Qualcomm CE users. This Chrome add-on simplifies the process of finding solutions by providing contextual and relevant information at the user's fingertips. The user-friendly interface ensures easy navigation and efficient interaction, making it an essential tool for anyone engaged in Qualcomm CE activities.

LangChain is a modular framework that helps developers create advanced AI applications by connecting large language models with external data sources and tools. It provides chain abstractions for sequential LLM calls, agent orchestration for decision-making workflows, memory modules for context retention, and integrations with document loaders, vector stores, and API-based tools. With support for multiple providers and SDKs in Python and JavaScript, LangChain accelerates the prototyping and deployment of chatbots, QA systems, and personalized assistants.

Legal MultiAgent System is a Python-based open-source platform that orchestrates multiple AI agents specialized for legal workflows. Each agent handles discrete tasks like document parsing, contract drafting, citation retrieval, compliance verification, and Q&A. Agents communicate via a central orchestrator, enabling parallel processing and collaborative analysis. By integrating with popular LLM APIs and allowing custom module development, it streamlines legal research, automates repetitive tasks, and ensures consistent output. The system’s modular architecture supports easy extension, so organizations can tailor agents to specific jurisdictions, practice areas, or compliance frameworks, achieving scalable and accurate legal automation.

Rebyte is a comprehensive AI platform that assists teams in boosting productivity. Leveraging Large Language Models (LLMs), it enables users to build generative AI applications and customized tools without requiring specialized data science knowledge. It provides a universal interface for various functionalities including question answering, task automation, and code execution. The platform is model-agnostic and supports enterprise data for robust performance.