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What is Android Use?

Action State Labs is dedicated to developing infrastructure specifically for native Android AI agents, highlighted by their open-source tool called Android Use, which enables smooth interaction between these AI agents and native Android applications by directly interfacing with the Android Accessibility Tree, thus eliminating the need for unreliable computer vision methods. This groundbreaking approach empowers AI agents to navigate and understand app user interfaces more swiftly and cost-effectively, achieving savings of up to around 95%, all while demonstrating increased resilience to user interface changes, thereby streamlining the automation of complex tasks including logistics, field operations, and other functions typically executed on native mobile platforms. Additionally, it provides an open-source core capable of functioning on local devices or emulators, along with a managed cloud option that offers auto-scaling features for enterprise applications, API endpoints, and extensive support services, which together facilitate developers in the efficient design, testing, and deployment of automation workflows driven by agents across numerous devices at the same time. The synergy of these capabilities distinctly establishes Action State Labs as a frontrunner in AI-powered automation for mobile applications, setting a new standard in the industry. Their commitment to innovation is further reflected in their ongoing enhancements and support for the developer community.

What is Agno?

Agno is an innovative framework tailored for the development of agents that possess memory, knowledge, tools, and reasoning abilities. It enables developers to create a wide array of agents, including those that reason, operate multimodally, collaborate in teams, and execute complex workflows. With an appealing user interface, Agno not only facilitates seamless interaction with agents but also includes features for monitoring and assessing their performance. Its model-agnostic nature guarantees a uniform interface across over 23 model providers, effectively averting the challenges associated with vendor lock-in. Agents can be instantiated in approximately 2 microseconds on average, which is around 10,000 times faster than LangGraph, while utilizing merely 3.75KiB of memory—50 times less than LangGraph. The framework emphasizes reasoning, allowing agents to engage in "thinking" and "analysis" through various reasoning models, ReasoningTools, or a customized CoT+Tool-use strategy. In addition, Agno's native multimodality enables agents to process a range of inputs and outputs, including text, images, audio, and video. The architecture of Agno supports three distinct operational modes: route, collaborate, and coordinate, which significantly enhances agent interaction flexibility and effectiveness. Overall, by integrating these advanced features, Agno establishes a powerful platform for crafting intelligent agents capable of adapting to a multitude of tasks and environments, promoting innovation in agent-based applications.

Media

Media

Integrations Supported

AG-UI
Oxylabs
Python
xpander.ai

Integrations Supported

AG-UI
Oxylabs
Python
xpander.ai

API Availability

Has API

API Availability

Has API

Pricing Information

Free
Free Trial Offered?
Free Version

Pricing Information

Free
Free Trial Offered?
Free Version

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Supported Platforms

SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Action State Labs

Date Founded

2025

Company Location

United States

Company Website

www.actionstatelabs.com

Company Facts

Organization Name

Agno

Company Location

United States

Company Website

github.com/agno-agi/agno

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