Document Retrieval
Learn how MINDTRICKS AI retrieves relevant information from your documents and knowledge base.
How Retrieval Works
Document retrieval is the process of finding and ranking the most relevant pieces of information from your indexed documents based on a query or question.
The Retrieval Process
- Query Processing: Your question is converted into a vector representation
- Similarity Search: The system finds document chunks with similar vectors
- Ranking: Results are ranked by relevance and semantic similarity
- Context Assembly: Top-ranked chunks are assembled as context for the AI
Vector Search
Our retrieval system uses advanced vector similarity search to find the most relevant information:
- Semantic understanding beyond exact keyword matching
- Context-aware search that understands meaning
- Efficient search across large document collections
- Real-time retrieval with sub-second response times
Improving Retrieval Quality
Best Practices
- Use clear, specific queries
- Include relevant context in questions
- Choose appropriate embedding models
- Organize documents logically
Common Issues
- Overly broad or vague queries
- Insufficient document context
- Mismatched embedding models
- Poor document segmentation