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SharePoint and OneDrive Connectors: File Upload Security

How and when Perplexity connects to SharePoint and OneDrive via API or indexed modes, without training models on your data

Written by Emilio Morales

Perplexity's SharePoint connector and OneDrive connector enable Enterprise Pro and Enterprise Max users to search their organization's SharePoint sites and OneDrive files directly through AI-powered natural language queries.

 

We have recently introduced a hybrid search architecture that addresses both data security concerns and scalability limitations through two distinct search modes: High-Precision Search (indexing-based) and Standard Search (API-based).

 

Search Architecture: Two-Tier Approach

Standard Search (API-Based)

How It Works:

  • Queries SharePoint/OneDrive directly via Microsoft's Search API at query time

  • No file copies stored in Perplexity infrastructure, aside from results found from queries (can be mitigated by data retention policy settings)

  • Searches across the user's entire SharePoint/OneDrive drive without file count limitations

  • Available to all Enterprise Pro/Max users immediately upon connector activation

Security Model:

  • Zero Data Retention: Files are not copied or stored in Perplexity systems, aside from results found from queries (can be mitigated by data retention policy settings)

  • Real-time Permissions: Respects SharePoint's/OneDrive’s native access controls dynamically

  • Minimal Data Copying: Only citation snippets included in answers are retained

  • No Model Training: Synced files are never used to train AI models

  • Immediate Access Revocation: When SharePoint/OneDrive permissions change, access is immediately reflected in Perplexity

Use Case: Organizations requiring maximum data privacy and minimal data footprint, especially for searching across millions of files at enterprise scale.

 

High-Precision Search (Indexing-Based)

How It Works:

  • Users select specific files/folders to sync for local indexing in Perplexity

  • Files are downloaded, parsed, and stored in dedicated AWS S3 buckets with vector embeddings in Vespa

  • Enables deeper semantic analysis and more comprehensive answers

  • File Limits: 500 files per project (Enterprise Pro), 5,000 files per Project (Enterprise Max)

  • Total User Limits: 15,000 files (Enterprise Pro), 50,000 files (Enterprise Max)

Security Model:

  • Dedicated Storage: Each organization's files stored in isolated AWS S3 "folders" with unique namespaces in Vespa vector storage

  • Encryption: AES-256 encryption at rest, TLS encryption in transit

  • Role-Based Access Control (RBAC): Minimum privilege access enforced across all systems

  • No Model Training: Synced files are never used to train AI models

  • Automatic Sync: File changes/deletions in SharePoint/OneDrive are automatically reflected in Perplexity

Use Case: Teams requiring maximum answer accuracy for frequently accessed documents, project-specific file collections, or collaborative projects with curated content.

 

Backend Architecture & Data Flow

Connection & Authentication

  • Admin Enablement: Organization admins enable SharePoint/OneDrive connector in Permissions settings

  • User Authentication: Users authenticate via OAuth 2.0 through Microsoft Entra (Azure AD)

  • Site Selection: Users select specific SharePoint sites to connect

  • Admin Consent: Microsoft admins may need to grant organization-wide consent for Perplexity app in Microsoft Entra

When Both Methods Are Active:

  • Perplexity queries both the local index and SharePoint API concurrently

  • Results are re-ranked to prioritize the most relevant sources

  • Citations link directly back to SharePoint for full file access

Indexing Process (High-Precision Search)

File Sync and Storage:

  1. File Selection: User selects files/folders through Perplexity UI

  2. Download: Files downloaded from SharePoint via Microsoft Graph API

  3. Storage: Raw files stored in AWS S3 with dedicated organizational namespaces

  4. Parsing: Text extraction from supported formats (PDF, DOCX, XLSX, PPTX, CSV, TXT, MD, JSON)

  5. Vectorization: Content converted to embeddings and stored in Vespa vector database

  6. Metadata Indexing: File metadata (name, path, permissions) indexed for search retrieval

  7. Removal: When a user disconnects SharePoint/OneDrive from Perplexity, they can choose to remove any indexed files

Security & Compliance Infrastructure

Permission Enforcement

SharePoint/OneDrive-Side Permissions:

  • If a user loses access to a file in SharePoint/OneDrive, that file is immediately removed from Perplexity

  • File deletions in SharePoint/OneDrive trigger immediate removal from Perplexity index

  • Users can only search files they have explicit SharePoint/OneDrive permissions to access

Perplexity-Side Permissions:

  • Admins control which users can access connectors via Organization settings

  • Files synced to projects are searchable by Project members, but file content requires SharePoint/OneDrive permissions

  • Session sharing respects organizational sharing policies set by admins

Best Practices

When to Use High-Precision Search (Indexing)

  • Project-specific file collections in projects

  • Frequently accessed knowledge base documents

  • Files requiring deep semantic analysis

  • Collaborative team environments with curated content

When to Use Standard Search (API-Only)

  • Searching across vast file repositories (millions of files)

  • Strict data residency and minimal data copying requirements

  • Exploratory searches across infrequently accessed files

  • Organizations with heightened security/compliance constraints