AI Agents
Agents with real jobs, not chat windows.
Volobox agents have handles, skills, personas, memberships, and managers. They answer questions, run playbooks, fill forms, analyze data, and take on assigned work, under rules you set.
Two kinds of agents
Your assistant, and your team's agents
Your personal assistant
- Private to you: conversations stay yours until you share one
- Works with your own context across the workspace
- Acts with your permissions, and asks you first
Shared team agents
- Belong to the workspace, with a handle, persona, and skill set
- Mention them with
$namein chat; assign them tasks and workflows - A manager approves actions beyond the requester's permissions
Shared agents are visible to team members, and they never see personal data.
Where they work
One agent, many surfaces
The same agent works 1:1, in team threads, on assigned tasks, inside workflows, and beside forms.
1:1 chat
Ask questions or delegate actions with streaming answers and approval cards.
Team mentions
Bring an agent into any project or task thread with a $mention.
Task assignment
Assign real work; coding tasks spawn a sandbox coding session.
Workflows
Markdown playbooks the agent executes step by step, with human decision points.
Form assist
Fill with AI: the assistant drafts complex forms field by field.
Data analysis
Agents run Python in a sandbox and save charts and outputs to your Drive.
Skills & commands
Build a role, not a prompt
An agent is a durable role, and skills are the parts it's built from: bundles of tools and instructions like Meeting Coordinator, Project Coach, Docs Curator, Request Handler, Web Reader, and Software Engineer. Add your own, import and export them as files, and wire parametric slash commands for repeatable prompts.
Knowledge
Your workspace is the context
Docs, tasks, requests, meeting notes, and PRs are automatically indexed. Agents answer with sources from your team's actual knowledge: no manual uploads, no separate RAG project, and the index stays inside your deployment.
Ecosystem
Packs, models, and MCP
Library packs
Install ready role agents (Release Manager, Delivery Coach, Tech Writer), or publish packs between workspaces and registries.
Learn moreMCP servers
Connect external tools (like GitHub) to your agents through the Model Context Protocol.
Learn moreGoverned by design
Ask vs Agent mode, approval cards, three authorization modes, rate limits, and audit, on every surface.
Learn moreBring your first agent onto the team.
We'll configure a shared agent for your real workflows during the demo.