beevibe-ai/beevibe

What it solves

Beevibe addresses the "private bubble" problem where AI agents used by individual team members operate in isolation. It prevents the loss of shared intelligence by providing a centralized workspace where AI agents and humans collaborate, ensuring that context and learned answers are compounded across the entire team rather than being repeated for every user.

How it works

Beevibe acts as an agent-native operating system that coordinates people and persistent AI agents through a shared team graph. It uses a control plane (API) and a shared memory layer (Postgres with pgvector) to manage tasks, ownership, and agent identities. To execute work, it utilizes local daemons installed on users' machines, which spawn and manage CLI-based AI tools (like Claude Code) using the user's own local files and tokens.

Who it’s for

It is designed for engineering teams and companies that use AI coding assistants and agents and want to transition from individual AI productivity to collective team intelligence.

Highlights

• Persistent Specialists: Agents have defined roles, hierarchy levels, and bounded memory that evolves over time.
• Agent-to-Agent Coordination: A "Mesh" layer allows agents to negotiate, ask other specialists for context, and escalate blockers to humans.
• Human-in-the-Loop: A web dashboard allows humans to review, redirect, and resolve blockers for AI agents.
• Self-Hosted: Users maintain full ownership of their data via a self-hosted Postgres database and Node services.