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What is Zooid?

Zooid is a collaborative messaging platform built on the Matrix protocol and offered as open-source software, featuring capabilities such as channels, threads, direct messaging, and designated spaces for team interactions. The platform supports self-hosting, which guarantees that all messages and user information are stored within the infrastructure that the operator controls. A standout feature of Zooid is its ability to incorporate AI agents directly within the same chat environments as human users, thereby fostering enhanced collaboration. Agents that adhere to the Agent Client Protocol (ACP), such as Claude Code, Codex, and opencode, can participate in discussions, with their contributions presented as structured interface elements rather than plain text; for example, permission requests manifest as approval cards, tool interactions are illustrated as structured data, task outlines are formatted as checklists, and sub-agent hierarchies are displayed as expandable trees. Furthermore, each AI agent functions within its own isolated sandbox to ensure security. Distributed under the MIT license, Zooid allows for comprehensive end-to-end self-hosting options, empowering users with the autonomy and control they desire over their communication environments. The combination of these innovative features positions Zooid as a highly attractive solution for teams eager to effectively harness the collaborative potential of both human participants and AI agents in their workflows. This makes it a versatile tool that can adapt to various organizational needs and enhance productivity through seamless integration of technology.

What is Future AGI?

Leverage our automated insights and customizable metrics to evaluate, improve, and continuously refine your GenAI models. Future AGI simplifies the process of assessing AI model outputs by automatically scoring them, which eliminates the need for manual quality assurance checks. Consequently, your QA team can focus their efforts on more strategic initiatives, potentially increasing their efficiency and capacity by as much as tenfold. This guarantees that interactions driven by AI remain consistently positive and in line with your brand identity. By optimizing your models, you can showcase the most relevant and engaging content tailored for each individual user. Furthermore, you have the ability to fine-tune your models to generate the most accurate summaries for your target audience. Future AGI enables you to create custom metrics that measure your AI model's accuracy based on the unique priorities of your specific use case. You can express your critical metrics in natural language, granting your QA team enhanced flexibility and authority in evaluating model performance. This approach ensures that your evaluations align with your business objectives, moving beyond traditional metrics like relevance to support a more thorough assessment framework. Embracing this strategy not only improves model performance but also cultivates a culture of ongoing enhancement within your organization. Ultimately, this commitment to refining your AI capabilities will significantly elevate the overall user experience and drive better outcomes for your business.

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Integrations Supported

Integrations Supported

Gemini Enterprise Agent Platform
Hugging Face
Microsoft Azure
OpenAI

API Availability

API Availability

Pricing Information

Free (open source)
Free Version

Pricing Information

Pricing not provided
Free Version

Supported Platforms

SaaS
On-Prem
Linux

Supported Platforms

SaaS
On-Prem

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Webinars
On-Site Training

Company Facts

Organization Name

Zooid

Date Founded

2026

Company Website

zooid.dev

Company Facts

Organization Name

Future AGI

Date Founded

2024

Company Location

United States

Company Website

www.futureagi.com

Categories and Features

Team Chat

Not specified

Categories and Features

Agentic AI

Not specified

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