Skip to main content

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

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 :
  1. Better contextualization: AI better understands relationships between similar documents
  2. More precise responses: Semantic search is more effective in a coherent corpus
  3. 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
Advantages: Combines project flexibility with thematic domain consistency

Good Naming Practices

Examples


Size and Number of Workspaces

Recommendations

Size OrganizationNumber of WorkspacesPrinciple
Small team (< 10)3-5 workspacesPer large area
Medium team (10-50)5-15 workspacesPer area and sub-area
Large organization (> 50)10-30 workspacesBy 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

  1. Define a clear and coherent knowledge domain
  2. Identify members working in this area
  3. Create with a descriptive name for the thematic content
  4. Document purpose (even if not used by the system, useful for admins)
  5. Start uploading or Sync with Datasource thematically-related documents

Maintenance

  1. Review members: Quarterly for standard workspaces
  2. Monitor consistency: Ensure that new documents remain thematically linked
  3. Clean up regularly: Remove obsolete documents to improve RAG quality
  4. Check usage: Identify under-used workspaces

Offboarding

  1. Inactivate user
  2. Remove the user’s membership from all their custom workspaces
  3. 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