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Description
Agno is a streamlined framework designed for creating agents equipped with memory, knowledge, tools, and reasoning capabilities. It allows developers to construct a variety of agents, including reasoning agents, multimodal agents, teams of agents, and comprehensive agent workflows. Additionally, Agno features an attractive user interface that facilitates communication with agents and includes tools for performance monitoring and evaluation. Being model-agnostic, it ensures a consistent interface across more than 23 model providers, eliminating the risk of vendor lock-in. Agents can be instantiated in roughly 2μs on average, which is about 10,000 times quicker than LangGraph, while consuming an average of only 3.75KiB of memory—50 times less than LangGraph. The framework prioritizes reasoning, enabling agents to engage in "thinking" and "analysis" through reasoning models, ReasoningTools, or a tailored CoT+Tool-use method. Furthermore, Agno supports native multimodality, allowing agents to handle various inputs and outputs such as text, images, audio, and video. The framework's sophisticated multi-agent architecture encompasses three operational modes: route, collaborate, and coordinate, enhancing the flexibility and effectiveness of agent interactions. By integrating these features, Agno provides a robust platform for developing intelligent agents that can adapt to diverse tasks and scenarios.
Description
Deeplake is an AI data runtime and GPU database built for teams developing agents, RAG systems, multimodal applications, robotics workflows, and generative media products. It is designed to solve the gap between GPU-powered AI models and CPU-bound data systems by keeping data closer to where AI workloads execute. The platform supports serverless Postgres, vector search, multimodal data storage, analytical workloads, and AI-optimized data lake functionality. Deeplake helps agents remember, retrieve, and act in fast cycles, making it useful for systems that need repeated context retrieval across long-running tasks. It can manage complex data such as video, images, point clouds, sensors, PDFs, audio, embeddings, model weights, and structured records. Developers can use familiar database concepts while gaining support for GPU-speed retrieval and scalable AI data operations. The platform is positioned for production-grade AI use cases where agents may generate databases, query thousands of times, and require faster memory access. Deeplake also supports private deployment patterns, including VPC environments, so organizations can keep sensitive data within their own infrastructure. With open-source adoption, enterprise security credentials, and a focus on agentic workloads, Deeplake helps AI teams build faster and more efficient data systems.
API Access
Has API
API Access
Has API
Integrations
AG-UI
Activeloop
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Dock
Ejentum
Google Cloud Platform
Hindsight
Jupyter Notebook
Integrations
AG-UI
Activeloop
Amazon SageMaker
Amazon Web Services (AWS)
ChatGPT
Dock
Ejentum
Google Cloud Platform
Hindsight
Jupyter Notebook
Pricing Details
Free
Free Trial
Free Version
Pricing Details
$0
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Agno
Country
United States
Website
github.com/agno-agi/agno
Vendor Details
Company Name
Activeloop
Founded
2018
Country
United States
Website
deeplake.ai/