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Lyzr is a low-code agent framework that adopts an agentic approach to building generative AI applications. It features fully integrated agents with pre-built RAG pipelines, enabling rapid development and deployment of various AI-driven applications such as chatbots, knowledge search tools, and workflow automation.
Lyzr is designed for Developers, CTOs, CPOs, and CIOs who value simplicity, rapid deployment, and data privacy in developing generative AI applications. It is particularly beneficial for those looking to integrate AI features in-house with a minimal learning curve.
With Lyzr, users can build chatbots, knowledge search engines, data analysis tools, RAG-powered applications, and multi-agent workflow automation. It also supports advanced uses like QA bots for FAQs and Text-to-SQL for database analysis.
Key features include locally deployable SDKs, private APIs, an AI Management System (AIMS). The platform ensures data privacy and compliance by running locally on the user's cloud.
Lyzr ensures data privacy and security by enabling local deployment on the customer’s cloud account. This setup helps enterprises maintain control over their data without compromising on compliance and latency issues.
Deploying an agent with Lyzr is straightforward, typically requiring just a few minutes. The framework’s low-code nature allows developers to set up agents with minimal coding, such as setting up a chatbot with only one line of code after initial setup.
Yes, Lyzr is often compared to platforms like Langchain, DSPy, and LlamaIndex. While these platforms use building blocks, programmatic, and modular approaches respectively, Lyzr uses an "agentic" approach that focuses on fully integrated, ready-to-launch agents.
Lyzr Automata is a multi-agent automation platform within Lyzr that focuses on workflow efficiency and effectiveness. It allows the creation and management of multiple agents assigned to specific tasks, promoting operational stability and performance.
Lyzr SDKs are downloadable as docker files and can be deployed locally on AWS, Azure and Google Cloud. The docker containers are tested for auto-scaling and can scale up from a few users to a million requests seamlessly.