It is an open-source platform designed to build, ship, and monitor agentic systems, enabling developers to create high-performance AI agents with memory, knowledge, and tools.
It is an open-source platform designed to build, ship, and monitor agentic systems, enabling developers to create high-performance AI agents with memory, knowledge, and tools. Agno provides a comprehensive environment for developing agentic systems, offering seamless integration with databases, vector storage, APIs, and more. Its workspaces allow users to go from concept to production in minutes, streamlining the development process.
Agno is model-agnostic, supporting any model from any provider, including closed models like OpenAI, Anthropic, and Cohere, as well as open-source models via platforms like Ollama, Together, and Anyscale. If a specific model or provider is missing, Agno commits to adding it within a week upon request. Similarly, it integrates with every major database and vector store on the market, such as Pinecone, LanceDB, and SingleStore, with the same promise to add any missing options within a week.
The platform includes an Example Gallery featuring in-depth examples and code for various use cases, ranging from basic agents and function calling to advanced fine-tuning and evaluations. Users can request specific examples, and Agno will add them to the gallery. Additionally, Agno Pro is offered free of charge to students, educators, and startups with less than $2 million in funding, with discounts available upon request.
Agno enhances the capabilities of large language models (LLMs) by incorporating memory, knowledge, and tools, enabling developers to build smarter and more efficient AI products. It is designed for performance and scalability, ensuring that agentic systems can handle demanding workloads. The platform is future-proof, model-agnostic, and optimized for speed, making it a versatile choice for developers aiming to stay ahead in AI innovation. Users can start building their agents today by visiting Agno’s website or GitHub repository.
"It is a fast and lightweight framework designed for creating decentralized agents with ease. The uAgents library, developed by Fetch.ai, enables the creation of autonomous AI agents in Python using simple and expressive decorators.
It is an experimental autonomous agent called ReactAgent that uses the GPT-4 language model to generate and compose React components from user stories.
It is a TypeScript library designed to create and orchestrate AI Agents, enabling developers to build, test, and deploy reliable AI applications at scale.
It is a comprehensive platform designed to enable developers to build, deploy, and scale production-ready AI agents quickly and securely using their own data.
It is a description of Oraczen, a company that provides AI solutions designed to empower enterprises by addressing inefficiencies in traditional monolith systems.
It is an AI-powered platform designed to streamline the software development lifecycle (SDLC) by automating repetitive tasks and enhancing engineering team productivity.
It is an AI-powered suite of tools designed to enhance software development workflows by integrating intelligent features across the entire software development lifecycle.
It is a serverless platform designed to provide AI virtual workstations, enabling developers to build and deploy AI agents capable of performing tasks typically done on a laptop.
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It is an AI-powered platform designed to assist product managers by generating Product Requirement Documents (PRDs), strategies, and insights in seconds, enabling them to enhance their productivity and impact.
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