The Challenge
Organizations accumulate vast amounts of unstructured and semi-structured data across documents, wikis, databases, and external sources. Finding relevant information quickly requires understanding context, relationships, and semantic meaning—not just keyword matching.
Traditional search solutions fall short because they lack:
- Semantic understanding of query intent
- Relationship-aware search across connected entities
- Contextual relevance based on user domain
- Multi-hop reasoning capabilities
- Integration of structured and unstructured data
The ArcadeDB Solution
- Knowledge Graph: Model entities and relationships as a native graph
- Vector Embeddings: Store semantic embeddings alongside entities for similarity search
- Hybrid Search: Combine graph traversal with vector similarity in single queries
- Multi-hop Reasoning: Find indirect connections through relationship chains
- Context-Aware: Filter results based on user role, domain, or permissions