As document libraries grow across teams and repositories, finding the right file often depends on remembering exact filenames or navigating complex folder structures. Contextual document search removes this friction by enabling semantic, intent-based search across documents—so users can find what they need based on meaning and content, not just labels.
By utilizing Appspace Intelligence, the platform processes document content and metadata to deliver highly relevant results, significantly improving time-to-information and overall user productivity.
How it Works
Contextual Document Search uses Appspace Intelligence to analyze document content and metadata, making documents searchable by context and intent.
- Contextual Search: Search within documents using keywords or natural language queries, with relevant matches highlighted directly in the content.
- AI-Generated Semantic Descriptions: Appspace Intelligence processes files to generate semantic descriptions that power more accurate, context-aware search results.
- Content and Metadata Analysis: Both document content and associated metadata are analyzed to deliver relevant results across connected repositories.
Supported File Types
The contextual document search supports the following file formats:
- DOCX
- XLSX
- PPTX
- Images
Key Benefits
Delivers measurable value for both users and organizations:
- Enables semantic, intent-based search without relying on exact filenames or folder structures.
- Supports natural language queries for faster and more intuitive discovery.
- Improves time-to-information and overall user productivity.
- Encourages consistent reuse of approved and trusted content.
- Enhances knowledge accessibility and discoverability across the Appspace platform.
Availability
Contextual Document Search will be available for documents stored in supported repositories within the Appspace platform. Support for additional file types and repositories may be expanded in future releases.