What is TeamBrain?
TeamBrain is a shared AI workspace for teams that want Claude, ChatGPT, or another AI client working from the same context. Teams upload docs, briefs, notes, and deliverables, then each person's AI can read and update the shared brain through MCP or the API while TeamBrain tracks files, changes, tasks, decisions, and reasoning. Knowledge is stored as plain Markdown and can be exported at any time.
Why TeamBrain works
AI chat history becomes a handoff problem the moment work leaves one person's window. TeamBrain gives every teammate and connected AI the same shared files plus the decisions and reasoning around them, so work can continue with the context already attached. It passes the reasoning forward instead of making the next person rebuild it from copied chats and scattered docs.
TeamBrain features
- Shared context for every AI. Each teammate's AI reads from and writes to the same shared brain, so updates made by one person become available to the rest of the team.
- Decision memory. TeamBrain records what changed, what was decided, who made the call, and the reasoning behind it, keeping the why attached to the work.
- MCP and existing AI clients. Teams keep using Claude, ChatGPT, and other AI clients. Any AI that supports MCP can connect directly, and TeamBrain also supports API connections.
- AI managed project workspace. Tasks, a Kanban board, calendar, comments, assets, dashboard, collections, and guest accounts sit in the same workspace, and connected AI can update the work.
- Markdown export and safeguards. Knowledge lives as plain Markdown that can be exported at any time. Deleted items stay in trash for 30 days, and TeamBrain says it does not train AI on team data.
- Morning priority nudge. Each morning, TeamBrain sends each person what is on their plate and what changed overnight, so the day starts with current priorities.
Who TeamBrain is for
- Founders and startup teams using several AI clients who want team context and decisions to outlive individual chat windows.
- Agencies managing client work with contractors and guests who need each workspace scoped to the people involved.
- Remote async teams where handoffs happen across time zones and the next person needs the reasoning behind past decisions.
- Freelancers and consultants working with clients who want files, tasks, comments, and AI context organized by project or client.
Similar micro SaaS ideas you can build
- Incident relay for engineering teams. A live incident record that keeps hypotheses, attempted fixes, decisions, and the current system state together. The next engineer can continue from the latest reasoning instead of repeating tests or reconstructing an outage from chat.
- Client approval memory for creative work. A tool that attaches every design or copy revision to the feedback and decision that caused it. New contractors can see what was rejected, what was approved, and why before making the next version.
- Decision trail for research projects. A focused research workspace that connects source notes to conclusions, rejected directions, and open questions. A teammate or AI can resume the investigation from the current thinking instead of rereading the entire research history.
