Main function: Parsed RAG collections
Paradigm workspaces are designed to organize and make accessible all types of unstructured documentation using a parsed RAG (Retrieval-Augmented Generation) collection architecture.
Important reminderThe workspace description in Paradigm is currently not used by the RAG system. It serves only as documentation for administrators. The RAG system relies solely on the content of the documents themselves.
What is a Parsed RAG Collection?
Each workspace contains a collection that :
- Automatically parses uploaded documents, whatever their format (PDF, DOCX, XLSX, images, etc.)
- Extracts and structures unstructured content to make it comprehensible to AI
- Generates embeddings for advanced semantic search
- Contextualizes answers based on all workspace documents
Key benefitThanks to RAG parsing, Paradigm can understand and query any technical, commercial, legal or operational documentation, even if it’s heterogeneous and unstructured. The system automatically transforms your documents into a searchable knowledge base.
Note: The workspace description is currently not used by the system and serves only as documentation for administrators.
Supported documentation types
RAG collections can parse and include:
- Technical documentation: specifications, API docs, architecture, code
- Business documents: procedures, guides, training, playbooks
- Legal resources: Contracts, NDAs, policies, compliance
- Customer data: Specifications, deliverables, communications
- Miscellaneous knowledge: Wikis, notes, presentations, spreadsheets
Organization Strategies
Recommended Approach: Organization by Knowledge Area
Since workspaces function as RAG collections, organize them by coherent knowledge domain rather than by organizational structure:
Principle of Thematic Coherence
Why it’s important: RAG works best when documents in the same workspace are thematically related. This enables :
- Better contextualization: AI better understands relationships between similar documents
- More precise responses: Semantic search is more effective in a coherent corpus
- Less noise: Avoids irrelevant results from different domains
Rule of thumb: if you’re asking “Will these documents be queried together in the same context?”, they must be in the same workspace.
Examples by Organization Type
▶1. Organization by Project (with thematic consistency)
When to use: Large projects with voluminous documentation and different types of audience
▶2. Organization by Functional Area
When to use: Teams with distinct areas of expertise and specialized documentation
▶3. Hybrid Organization (Recommended)
Advantages: Combines project flexibility with thematic domain consistency
Good Naming Practices
Examples
Size and Number of Workspaces
Recommendations
| Size Organization | Number of Workspaces | Principle |
|---|
| Small team (< 10) | 3-5 workspaces | Per large area |
| Medium team (10-50) | 5-15 workspaces | Per area and sub-area |
| Large organization (> 50) | 10-30 workspaces | By area, team and project |
When to create a new workspace
Practical Use Cases
1. Consistent Multi-Project Documentation
Scenario: Several projects sharing the same technical stack
Solution:
RAG advantage: The system can respond to common patterns by drawing on all projects.
2. Customer Knowledge Base
Scenario: Agency managing several customers
Solution:
RAG advantage: Perfect isolation by customer + reusable methodologies
3. Compliance Documentation
Scenario: Multiple regulatory requirements
Solution:
RAG Advantage: Precise search by regulatory framework
4. Onboarding and Training
Scenario: Training documentation by role
Solution:
RAG Advantage: Customized responses by user role
Workspace Lifecycle
Creation
- Define a clear and coherent knowledge domain
- Identify members working in this area
- Create with a descriptive name for the thematic content
- Document purpose (even if not used by the system, useful for admins)
- Start uploading or Sync with Datasource thematically-related documents
Maintenance
- Review members: Quarterly for standard workspaces
- Monitor consistency: Ensure that new documents remain thematically linked
- Clean up regularly: Remove obsolete documents to improve RAG quality
- Check usage: Identify under-used workspaces
Offboarding
- Inactivate user
- Remove the user’s membership from all their custom workspaces
- Transfer ownership of workspaces if necessary
Audit and Traceability
Workspace events :
- Creation
- Modification (name, description)
- Add/remove members
- Delete
Documents events :
- Upload
- Consult through tools (docsearh, etc.)
- Delete
Access events:
- Access attempts denied
- Permission changes
- Data export