GBrain

GBrain is a collaborative artificial intelligence platform designed to centralize the workflow of technical and product teams within a single operating environment. Unlike individual chat interfaces, this tool allows an entire team to work together in the same conversation, sharing context, notes, and access to various language models such as ChatGPT, Claude, Cursor, or Codex.

GBrain operates by creating a shared memory for the entire organization. Instead of each team member training their own AI separately, the tool uses Markdown files that are accessible and editable by users. This technology ensures that any correction or new instruction is instantly synced across all connected AIs, eliminating information silos and ensuring that responses remain consistent with the company's internal processes.

The technical architecture of GBrain stands out for its integration with the Model Context Protocol (MCP) and its ability to connect to external tools through a single configuration for the entire team. Its core capabilities include:

• Advanced permission management: Allows for the connection of Gmail, Google Calendar, Slack, Stripe, or GitHub accounts, granting specific access levels (read-only or management) for each AI model without sharing passwords.
• Automation through Skills: Includes pre-configured functions that execute recurring tasks autonomously, such as the Team Standup to summarize daily activity or Inbox Cleanup to archive irrelevant emails.
• Activity tracking: All actions performed by the AIs are logged, allowing for audits of which model executed each task and under which permissions.
• Multi-platform synchronization: The context generated in the workspace can be transferred to development environments, such as the computer terminal or specialized code editors.

This tool is especially useful for startups and development teams that need to optimize productivity and maintain control over their data ownership. GBrain facilitates the creation of efficient AI workflows, allowing the artificial intelligence to learn the company’s communication tone and manage tedious administrative tasks, such as converting support chats into support tickets or conducting preliminary research on profiles for meetings.

By centralizing the use of enterprise AI, teams can scale their operations without losing knowledge when a member works in isolation. The user maintains custody of all keys and ownership of the generated memory at all times, with the option to run the platform on private servers for enhanced security.