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What is kubbi?

Kubbi functions as a protective intermediary specifically built for AI agents, enabling the secure exchange of data, files, and execution outputs among diverse systems, agents, or individuals through temporary, encrypted claim links. Instead of delivering sensitive information directly through workflows, prompts, or logs, Kubbi allows a content producer to create a payload that contains the required data or packaged files, assigns a time-to-live, and generates a unique claim URL for the subsequent participant in the process. The recipient is then able to retrieve the payload at their own convenience, with the option for the data to expire automatically or be deleted permanently based on predetermined access limits. This approach significantly reduces the likelihood of exposing sensitive data across different systems and prevents any unintentional logging, caching, or replaying of the information. Additionally, Kubbi is adaptable, supporting a range of scenarios such as the transfer of configuration files, datasets, reports, tokens, and any other sensitive or temporary data that should not linger within systems. By utilizing such a secure transfer mechanism, Kubbi ensures enhanced data integrity and confidentiality throughout the entire workflow, promoting trust and security among all participants involved. This innovative solution not only streamlines data sharing but also fortifies privacy, making it a crucial tool in today's data-driven environments.

What is Oqoqo?

Oqoqo is an all-encompassing platform designed for the development of evaluations and customized benchmarks for practical tasks requiring agency, allowing teams to carry out extensive experiments in realistic environments through fully managed cloud services. Users are empowered to create private collections of tasks and assessment criteria, evaluating agents on their interactions with a variety of products, including skills, MCP servers, CLIs, SDKs, APIs, documentation, and files, while also enabling comparisons among agents, models, interventions, and levels of effort under controlled conditions. Each task is executed within its own distinct environment, equipped with the essential project state, context, files, tools, and credentials needed for seamless operation. Oqoqo carefully tracks every detail of each execution, recording commands, tool interactions, errors, files, and the specific moment when an agent fails, ultimately yielding metrics such as pass or fail outcomes, pass rates, improvements, token usage, and friction points. These insightful metrics allow teams to identify problems within product interfaces, tackle token inefficiencies, scrutinize performance differences, correct failures, and re-run experiments for additional refinement and learning. This ongoing process cultivates an atmosphere of continuous enhancement, ensuring that agents are perpetually refined for maximum effectiveness, while also fostering collaboration and knowledge sharing among team members. Such an environment not only improves agent performance but also drives innovation within the team.

Media

Media

Integrations Supported

Model Context Protocol (MCP)
Python
TypeScript

Integrations Supported

Model Context Protocol (MCP)
Claude Code
Codex CLI
Cursor
GitHub Copilot
Grok Build
Hermes Agent
OpenClaw
OpenCode
Pi Agent

API Availability

Has API

API Availability

Has API

Pricing Information

$19 per month
Free Version

Pricing Information

$20 per month
Free Version

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Web-Based Support

Customer Service / Support

Web-Based Support

Training Options

Documentation Hub

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

kubbi

Company Location

United States

Company Website

www.kubbi.ai/

Company Facts

Organization Name

Oqoqo

Date Founded

2026

Company Location

United States

Company Website

oqoqo.ai/

Categories and Features

Agentic AI

Not specified

Categories and Features

Agentic AI

Not specified

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