The workspace where people and agents work as one team.

Projects, chat, docs, and meetings in one workspace. With AI agents you can assign tasks to, mention in chat, and trust to write code. Every action is permissioned, approved, and audited.

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We run our own company on Volobox · Cloud or on-premise · Bring your own models

Home: your day at a glance

The problem

Your work lives in five tools. Your AI lives in none of them.

Today it's trackers, chat apps, wikis, and drives, with AI tools bolted onto the side. Chatbots that answer but don't act. Coding agents that act but can't be seen or governed. Volobox was built as one place for your team and your agents.

Task to PR

Assign a task to an AI engineer. Get a pull request back.

Agents in Volobox take on all kinds of work: playbooks, data analysis, everyday tasks. Coding is the clearest proof, and it happens fully in the open: unlike black-box coding agents, you see every step, every file, every question.

  1. 1

    Assign the task to an agent

    Pick an agent as assignee on any project task, like a teammate.

  2. 2

    A sandbox boots, the agent plans

    An isolated VM clones your repo; the agent reads the task and its thread.

  3. 3

    Watch it code, live

    Diffs, terminal, and per-turn cost stream in. Questions land in the task discussion.

  4. 4

    Review in-app

    Comment on lines, request changes. Feedback goes straight back to the agent.

  5. 5

    The PR ships

    Commit, push, pull request, branch preview: linked to the task that started it.

Agents as teammates

Meet your new teammates.

Every user gets a personal assistant. Teams add shared agents with their own handles, personas, and skill sets. Mention them in chat with $name, assign them to tasks, or hand them a workflow.

  • Character, skills, and permissions configured per agent
  • Parametric slash commands for repeatable prompts
  • Whatever you can do, an agent can do, with your approval
  • Teammates can watch and join agent conversations

Trust & control

Autonomy you can audit.

This is the part everyone else is still improvising.

User-delegated

The agent acts as you, with your permissions, and every write asks first with an approval card.

Manager-escalated

When the requester's permissions aren't enough, the agent's manager approves, or a standing rule pre-approves within a budget.

Self-authorized

The agent holds its own memberships like an employee and works alone inside them, under hard rate limits.

Plus Ask mode (read-only) vs Agent mode, standing auto-approval rules with budgets, a full audit log, and execution traces for every run.

People first

Designed for people first. AI makes it faster, not stranger.

Volobox is a complete, fast workspace even with AI switched off. Adopt agents at your own pace: start with read-only Ask mode, add approvals, then grant autonomy where it earns it.

Keyboard-first workbench with browser-style tabs, voice input and writing assist, and no forced AI anywhere.

Deployment & data

Your data. Your models. Your servers, if you want.

Run Volobox in the cloud or on-premise. Workspace knowledge is indexed for agents inside your deployment. It never leaves your control.

Bring your own models, with your own keys

  • Claude
  • GPT
  • Gemini
  • Kimi
  • Open-source models you host

Coming from Jira + Slack + Notion + Copilot?

Here's what changes.

ElsewhereVolobox
AI assists: it summarizes, drafts, and updates fields.AI executes: task in, pull request out, with the human in the loop.
Guardrails are a toggle or a checkpoint.A three-mode authorization model with approval cards, budgets, and hard rate limits.
Black box: you see the result, not the work.Glass box: live terminal, diffs, plans, questions, cost, and a full audit trail.

Questions teams ask first

What stops an agent from doing something destructive?

Every write action goes through the authorization model: approval cards by default, manager escalation when permissions are missing, and hard rate limits even for self-authorized agents. Everything is logged and traceable.

Full answer
Which AI models can we use?

Models come set up on a cloud workspace, so you can start without a provider account. You can also connect your own keys, including OpenAI, Anthropic, Google, Moonshot AI, OpenRouter, and OpenAI-compatible endpoints you host.

Full answer
Can we run Volobox on our own servers?

Yes. Volobox deploys to your cloud or fully on-premise, with your own model endpoints. Workspace knowledge indexing stays inside your deployment.

Full answer
Do we have to use the AI features?

No. Volobox is a complete workspace on its own. Many teams start with projects, chat, and docs, then enable agents gradually, read-only first.

Full answer
How is pricing and usage measured?

We're onboarding teams through guided demos right now. Request a demo and we'll walk through packaging for your team size and deployment.

Full answer

See a real agent close a real task on your stack.

A 30-minute walkthrough with your use cases, not a canned pitch.