Qorqbot for Windows

Qorqbot for Windows

Qorqbot for Windows is a proactive AI agent platform developed by 49 Agents that helps users automate complex business workflows, coordinate AI agents, and manage long-running tasks from a centralized interface. The software runs locally through Windows Subsystem for Linux 2 (WSL2) with Ubuntu 24.04, providing access to its dashboard through a Windows web browser. Qorqbot works with existing AI coding and agent subscriptions, including OpenAI Codex and Claude Code, instead of requiring users to adopt a single AI model provider. The platform combines agent orchestration, shared context, business integrations, custom workflows, and approval controls to help AI agents complete work across multiple steps. Users can connect supported communication services, customer relationship management systems, and other business tools while maintaining oversight of sensitive actions. Qorqbot is free for personal and qualifying noncommercial use, with commercial licensing available for businesses and professionals.

AI agent automation and orchestration highlights

• Run proactive AI agents that manage complex, multistep business tasks and continue working in the background.
• Use existing AI subscriptions and agent tools, including OpenAI Codex and Claude Code, through a provider-agnostic architecture.
• Coordinate multiple AI agents with shared context, operational tools, and customizable workflows.
• Connect supported email, communication, CRM, and business applications through integrations and Model Context Protocol tools.
• Review important decisions and approve sensitive actions before AI agents proceed.
• Operate Qorqbot locally through WSL2 on Windows, with a browser-based dashboard for monitoring agents and tasks.

Proactive AI agents for Windows

Qorqbot provides Windows users with an AI agent platform designed to manage complex work rather than simply answer individual prompts. The software helps users organize tasks, coordinate AI tools, and maintain continuity across ongoing workflows.

Its proactive approach is useful for business operations, research, administrative processes, and other activities involving multiple steps. Agents can work toward defined objectives while users review progress and intervene when necessary.

Windows Subsystem for Linux integration

Qorqbot runs on Windows through Windows Subsystem for Linux 2, commonly called WSL2. The supported configuration uses Ubuntu 24.04 as the Linux environment for running the software.

WSL2 allows Windows users to operate Qorqbot without maintaining a separate physical Linux computer. The agent runtime operates inside Ubuntu while the dashboard is accessed through a Windows browser.

Browser-based dashboard

Qorqbot provides a dashboard for interacting with agents and reviewing ongoing work. Windows users can open the interface in a compatible web browser after starting the local runtime.

The dashboard provides a centralized place for conversations, agent navigation, and task management. This helps users monitor activity without constantly switching between command-line sessions.

Provider-agnostic AI architecture

Qorqbot is designed to work with multiple AI providers rather than depending on a single proprietary language model. Users can connect supported AI tools according to their existing subscriptions and preferences.

A provider-agnostic architecture is useful for organizations that want flexibility in their AI infrastructure. It also allows users to experiment with different models and agent systems.

OpenAI Codex integration

Qorqbot supports using OpenAI Codex as an underlying agent through its command-line interface. Users can connect an existing Codex environment to the Qorqbot operational layer.

Codex integration is useful for tasks involving software development, automation, and technical workflows. Users must install and authenticate the supported Codex CLI separately.

Claude Code integration

Qorqbot supports Anthropic Claude Code as an underlying agent. Users can install Claude Code in their WSL2 environment and connect it to Qorqbot.

Claude Code integration is useful for coding tasks, technical research, and agent-driven workflows. Qorqbot adds coordination and business-oriented tools around the existing agent.

Existing AI subscriptions

Qorqbot is designed to work with AI subscriptions users already pay for. This approach reduces the need to replace established AI tools when adopting the platform.

Existing subscription support is useful for individuals and businesses with established AI workflows. Access to particular models depends on the connected provider and its subscription terms.

AI agent orchestration

Qorqbot provides an operational layer for coordinating AI agents across complex tasks. Users can organize activities that involve multiple tools, steps, and decisions.

Agent orchestration is useful for workflows that require more than one AI interaction. It helps connect individual agent actions into a broader process.

Multi-agent coordination

Qorqbot supports workflows involving multiple AI agents. Agents can contribute to different parts of a task while operating within a shared work environment.

Multi-agent coordination is useful for processes involving research, analysis, drafting, and execution. It can reduce the amount of manual coordination required between separate agent sessions.

Background task execution

Qorqbot is designed to carry complex and long-running work forward in the background. Agents can continue progressing through supported workflows while users focus on other activities.

Background execution is useful for tasks that require multiple stages or extended processing. The local runtime and required services must remain available for work to continue.

Long-running business workflows

Qorqbot supports workflows that extend beyond a single chat interaction. Users can establish objectives that require information gathering, tool usage, and multiple decisions.

Long-running workflows are useful for business processes such as preparing outreach, updating records, and coordinating operational activities. Results depend on the available integrations and configured agent capabilities.

Shared agent context

Qorqbot provides context-management capabilities that help agents work with relevant information. Shared context can include operational instructions, business details, and information needed to complete tasks.

Context management is useful for reducing repeated explanations. It helps agents operate with a more consistent understanding of the user's objectives.

Adaptive personalization

Qorqbot includes a self-learning system designed to adapt to user preferences and working methods. The platform can incorporate information about processes, organizational structures, and preferred ways of completing tasks.

Personalization is useful for recurring workflows. Users should review the context and instructions available to agents to maintain accuracy.

Business process automation

Qorqbot helps users automate supported business processes through AI agents and connected tools. Workflows can combine information retrieval, drafting, analysis, and operational actions.

Business process automation is useful for repetitive administrative tasks and multistep operations. The scope of automation depends on the configured integrations and permissions.

Custom AI workflows

Qorqbot supports creating workflows tailored to individual business requirements. Users can organize agent activities around recurring tasks and operational procedures.

Custom workflows are useful for businesses with specialized processes. They allow the platform to reflect how an organization actually works.

Custom agent skills

Qorqbot provides a plug-and-play architecture for adding custom skills to its agent environment. Skills can extend the actions and knowledge available to connected agents.

Custom skills are useful for specialized tasks that require repeatable instructions or additional capabilities. Their behavior depends on implementation and configuration.

Plugin architecture

Qorqbot supports plugins and extensions for expanding its functionality. Users can connect additional capabilities without replacing the underlying agent system.

Plugins are useful for adapting the platform to different operational requirements. Available integrations depend on the current software version and installed components.

Model Context Protocol support

Qorqbot incorporates Model Context Protocol, or MCP, tools into its agent architecture. MCP provides a standardized approach for connecting compatible AI agents with external tools and data sources.

MCP support is useful for extending agent capabilities across applications. Users can configure compatible tools according to their workflows and security requirements.

Email integrations

Qorqbot is designed to work with supported email services, including Gmail and Outlook integrations. Connected agents can use available tools to assist with communication workflows.

Email integration is useful for preparing outreach, reviewing correspondence, and coordinating follow-up activities. Specific actions depend on the configured connectors and their permissions.

CRM workflows

Qorqbot supports business workflows involving customer relationship management systems. Agents can work with CRM-related information through available operational tools.

CRM integration is useful for sales operations, customer management, and administrative processes. Supported actions depend on the connected CRM and available integration capabilities.

Communication tools

Qorqbot's architecture includes support for connecting communication services through compatible tools. The project's interface illustrates workflows involving messaging and phone-related services.

Communication integrations are useful for coordinating business activities across different channels. Individual connectors may require separate setup or development.

Task planning

Qorqbot helps agents organize complex objectives into actionable steps. Users can define work and allow supported agents to progress through the required activities.

Task planning is useful for processes involving dependencies and multiple deliverables. Users retain the ability to review important decisions.

Agent task delegation

Qorqbot supports coordinating work among multiple agents. Different agents can contribute to research, drafting, analysis, or operational tasks.

Task delegation is useful when a workflow contains distinct activities. The platform provides an operational interface for coordinating agent contributions.

Approval workflows

Qorqbot includes signoff controls for actions and decisions that require human attention. Agents can prepare work and present important decisions for approval.

Approval workflows are useful for maintaining oversight of sensitive business operations. They allow users to review proposed actions before execution.

Human-in-the-loop automation

Qorqbot combines autonomous agent activity with human supervision. Users can allow agents to handle routine work while retaining control over important decisions.

Human-in-the-loop automation is useful for workflows involving business judgment, customer communications, or consequential changes. It provides a way to balance efficiency with oversight.

Agent activity monitoring

Qorqbot provides an interface for viewing agent activity and ongoing tasks. Users can review progress and interact with agents through the dashboard.

Activity monitoring is useful for understanding what agents are doing. It reduces the need to manually inspect separate terminal sessions.

Terminal-based agents

Qorqbot works with supported command-line AI agents running in the local environment. These agents provide underlying reasoning and execution capabilities.

Terminal integration is useful for developers and technically oriented users. It allows Qorqbot to build on established CLI-based AI workflows.

Local execution

Qorqbot runs on the user's own computer rather than requiring a fully hosted agent environment. On Windows, the runtime operates inside WSL2.

Local execution provides control over the environment in which agents operate. External AI providers and connected services may still process data according to their own policies.

Data privacy

Qorqbot emphasizes local execution and user control over agent data. Its licensing and account systems are separate from the underlying AI providers.

Local operation is useful for users who prefer to manage their own computing environment. Privacy also depends on the AI services, integrations, and permissions used with the platform.

Open development

Qorqbot maintains a public source repository on GitHub. Users can inspect available code, follow development, and review project documentation.

Public source availability provides transparency into the software's implementation. Qorqbot uses a source-available noncommercial license rather than an unrestricted open-source license.

Early-access development

Qorqbot is an early-access product developed and used for operational workflows. Its features and integrations may evolve as development continues.

Early-access software is useful for users interested in emerging agent technology. Organizations should test important workflows before relying on them for production operations.

Windows installation

Qorqbot for Windows requires WSL2 with Ubuntu 24.04. Users install Python 3.12, the Python virtual environment package, Git, and tmux inside Ubuntu, then install and authenticate a supported agent CLI such as Codex or Claude Code.

The software is distributed as a Linux archive that runs inside WSL2 rather than as a conventional native Windows executable. Users extract the package into their Ubuntu home directory, start the runtime, and access the dashboard through their Windows browser.

Windows compatibility and pricing

Qorqbot supports Windows computers with Intel or AMD processors capable of running WSL2 and Ubuntu 24.04. The software requires the appropriate Linux dependencies and at least one configured AI agent CLI.

Qorqbot is free for personal use, education, and qualifying noncommercial organizations. Commercial use is free through December 31, 2026, after which a commercial license is required. The published commercial price is $10 per user per month when billed annually, while monthly billing costs more. AI provider subscriptions may involve separate charges.

Alternative to consider

• OpenClaw — an AI agent platform that connects language models with messaging services, automation tools, and external applications to perform multistep tasks.