What is an AI Workspace?
An AI Workspace is a scoped AI environment inside an organization. It owns its own knowledge base, assistant instructions, Business Tools, and conversations. Unlike a single shared chatbot, workspaces keep Support, HR, IT, and other teams from mixing policies, tools, and chat history.
In Qefro, every Customer AI and Employee AI experience binds to one or more workspaces you configure in the Admin Console.
Short definition (citation-ready)
An AI Workspace is an isolated context for retrieval-augmented assistants and tool calls: documents, instructions, connectors, and conversations stay inside that workspace unless you deliberately share them.
Why AI Workspaces exist
Organizations rarely need “one bot for everything.” They need:
| Need | Workspace answer |
|---|---|
| Different audiences | Customer Support vs Internal HR |
| Different knowledge | Public FAQs vs confidential policy |
| Different tools | Order lookup vs payroll APIs |
| Different permissions | Widget visitors vs authenticated employees |
Without workspaces, a single chatbot index becomes a privacy and accuracy risk: internal docs leak into customer answers, or tools meant for staff become callable from a public widget.
Core components
| Component | Role |
|---|---|
| Knowledge | Uploaded files, crawled sites, OCR — indexed for hybrid RAG |
| Instructions | Tone, language, refusal rules, product voice |
| Business Tools | REST / OpenAPI connectors with encrypted credentials |
| Business Actions | Runtime tool invocations during a conversation |
| Conversations | Channel-bound chat history for that workspace |
| Channels | Website widget, WhatsApp, Internal Portal |
Architecture
Organization
Billing, members, branding, and the publishable widget token.
AI Workspace
Isolated knowledge, tools, instructions, and conversations.
RBAC + Teams
Members only see workspaces they are granted.
AI Workspace vs related ideas
| Concept | How it differs from an AI Workspace |
|---|---|
| AI chatbot | Often one bot + one knowledge dump; weak multi-team isolation |
| Custom GPT / project | Usually personal or single-team; not a multi-tenant org platform |
| Helpdesk ticket bot | Focused on tickets; may lack employee portal + general RAG workspaces |
| Agent framework | Code-first orchestration; Qefro workspaces are productized with Admin Console + channels |
See also: AI Workspace vs AI Chatbot.
How Qefro implements AI Workspaces
- Sign up at app.qefro.com and create an organization (tenant).
- Create workspaces for each use case (Support, HR, IT, …).
- Ingest knowledge (
POST /api/v1/documents) and configure instructions. - Attach Business Tools when the assistant must call APIs.
- Bind channels: website widget, WhatsApp, or Internal Portal.
Admin Console APIs expose workspaces under /api/v1/org/workspaces. Day-to-day console operations also use GraphQL on api.qefro.com.
Workflow
Stand up one AI Workspace
- Name the audience — Customer-facing or employee-only?
- Create the workspace — Name it after the team or use case.
- Ingest knowledge — Upload docs or crawl approved URLs; verify citations.
- Add tools carefully — Start read-only; encrypt secrets; review logs.
- Bind a channel — Widget, WhatsApp, or Internal Portal with RBAC.
Best practices
- One primary audience per workspace (do not mix public FAQs with confidential HR).
- Prefer citations and refusals over guessing when knowledge is thin.
- Scope Business Tools to the minimum HTTP methods and paths required.
- Use Teams so Members only access granted Employee AI workspaces.
- Monitor analytics, feedbacks, and tool execution logs before expanding channels.
Common misconceptions
| Myth | Reality |
|---|---|
| “An AI Workspace is just a chatbot skin.” | Workspaces isolate knowledge, tools, and conversations — not only UI. |
| “One workspace for the whole company is fine.” | Cross-team mixing increases leakage and wrong-tool risk. |
| “RAG alone is enough.” | Production assistants also need authz, SSRF controls, and identity forwarding for actions. |