---

Screenshots

---

Details

---

---

EdgeQuake Main Features

• Fast at scale
  Handles large document collections quickly, avoiding slow processes as your data grows.
• Designed for teams
  Built for teams who want high-quality Graph-RAG answers without fragile pipelines or hidden processes.
• Full stack in Rust
  Runs completely on Rust and PostgreSQL, without needing Python or cloud services.
• Handles complex PDFs
  Works well with difficult PDFs like multi-column pages, images, or scanned documents.
• Multiple query types
  Supports different methods to answer simple or complex questions with the best retrieval approach.
• Multi-tenancy support
  Keeps data separate for different projects to prevent mixing or losing context.
• Cost-effective retrieval
  Reduces the need for expensive remote API calls, saving money and avoiding slowdowns when APIs are busy.
• Multiple retrieval modes
  Supports local, global, hybrid, naive, mix, and graph-aware ways to find information.
• Avoids lost relationships
  Keeps track of how different data parts depend on each other to give accurate answers.
• Lineage-aware knowledge graphs
  Converts PDFs, markdown, and raw text into graphs that show how data is connected and related.
• Overcomes traditional RAG issues
  Provides better answers by understanding relationships, traceability, and data connections, unlike simple similarity search.

---

Verified Badge

---

EdgeQuake Alternatives

---

Technologies Used

View All Technologies