Shared AI memory
A shared folder of plain Markdown files stores information about people, projects, decisions, and other team knowledge. Connected AIs can read and write to the same files, and the folder can be copied as an export.
GBrain
GBrain is a shared AI workspace for teams using multiple models and AI clients. It combines shared Markdown-based memory, controlled connections to email, calendars and web tools, and scheduled skills for recurring research, communication and content workflows.
Shared context and controlled AI workflows
GBrain is a shared AI workspace for teams that use multiple AI models and clients. It combines a common memory, connected accounts and preconfigured skills so work can continue from the same context instead of being rebuilt separately in each AI application.
The workspace stores its memory as plain Markdown files covering topics such as people, projects and decisions. ChatGPT, Claude, Cursor, Claude Code and other connected AIs can use that memory, while GBrain provides controls for account permissions, daily tool limits and records of activity. Teams can also schedule skills that summarize work, research people, clean inboxes, process media, check claims or extract structured data.
Core features
Centralized tools
Connect accounts such as Gmail, Google Calendar, Stripe, web search, and page-fetching services once. GBrain mediates requests so connected AIs receive results without receiving the underlying password or key.
Permissions and limits
Set each AI's access to a connected account from Off through read or full access, and apply daily call limits to tools. Changes take effect on later calls and activity is recorded in a shared log.
Multi-AI workspace
Use models from Anthropic and OpenAI in the same workspace and switch between them. The workspace is also described as working with ChatGPT, Claude, Cursor, Claude Code, and other AI clients.
Scheduled skills
Turn on finished workflows with a short setup, then run them once or on a schedule. Available examples include team daily syncs, research briefs, meeting notes, fact checking, transcript creation, news monitoring, and structured data pulls.
Multiplayer collaboration
Use the workspace with a team rather than separate per-person accounts. Members share the conversation and memory, while the underlying workspace provides the connected services and activity record.
Practical use cases
Coordinate daily team work
A team can run Team Daily Sync against work from sources such as GitHub, Gmail and Google Calendar, then send a daily summary to the team. Shared memory gives the workspace a place to retain relevant context beyond a single conversation.
Prepare for people-focused meetings
Before a meeting, Deep Person Brief can combine public research with the team's notes to produce a sourced briefing on a candidate, guest or investor. This supports preparation without asking each AI to reconstruct the background separately.
Reduce recurring inbox work
Inbox Cleanup can learn which messages are routinely ignored and archive them on a schedule, while connected email permissions determine what the workflow may read or change.
Review claims and research
Fact Check and Study Check can review claims against live sources or original research and return a report or verdict. These workflows are suited to editorial, research and publishing tasks where source traceability matters.
Convert unstructured material into usable records
Meeting Notes, Clean Transcript, Podcast Notes and YouTube Notes can turn recordings or videos into searchable written material, while Structured Data Pull extracts selected fields from emails, documents and web pages into a deduplicated table linked to sources.
Pros and Cons
Pros
- One memory can be shared across multiple AI clients and exported as a folder of Markdown files.
- Team members use one workspace and shared conversation without an additional per-seat charge described in the pricing information.
- Connected account credentials stay with GBrain rather than being passed to each AI, while permissions and daily limits can be adjusted.
- Skills turn recurring tasks into on-demand or scheduled workflows with outputs delivered to a thread, email or Slack.
- The workspace supports models from Anthropic and OpenAI and can connect email, calendars and web-based tools.
Cons
- Usage credit covers AI models and metered tools, so heavy usage may require buying additional credit.
- Setting up useful workflows requires connecting accounts and choosing permissions for the AIs and tools involved.
- The documented integrations and capabilities are centered on the accounts and AI clients supported by the workspace; the source does not establish universal compatibility.
FAQ
How do you get started with GBrain?
Sign in with Google. The workspace is described as running in about two minutes, with no software installation required. Accounts such as Gmail or a calendar can then be connected and assigned access levels for the AIs that use them.
Can a team use the same GBrain workspace?
GBrain provides one shared workspace for the team. Invited members use the same conversation and shared memory, and adding team members does not add a per-seat charge according to the pricing information.
How does GBrain control access to connected accounts?
The workspace can connect email, calendars, and web services. GBrain keeps the account sign-in, while each AI receives the result of an allowed call rather than the password. Access can be set from Off through read or full access, depending on the connected account.
What can GBrain skills produce?
Skills are preconfigured jobs that can run on demand or on a schedule. Depending on the skill, results can be sent to the workspace thread, email, or Slack. Examples include meeting notes, inbox cleanup, research briefs, fact checking, and structured data extraction.
How does usage credit work?
The workspace includes $100 of monthly usage credit for AI models and metered tools such as web search and page crawling. If the credit is used, additional credit can be purchased from the workspace billing page; the site says users are notified before reaching the limit.
Quick Facts
- Category
- AI workspace and productivity platform
- Primary users
- Teams working with multiple AI tools
- Memory format
- Plain Markdown files in a shared workspace folder
- AI and model support
- Anthropic and OpenAI models; ChatGPT, Claude, Cursor and Claude Code connections are described
- Connected services
- Email, calendar, web search and page-fetching tools, with Gmail, Google Calendar, Stripe, Exa and Firecrawl shown
- Access model
- Browser workspace with connected clients, terminal and MCP workflows described
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