SendQuery
Your agent or RAG pipeline sends a query directly to Perseus, acting as the intelligent retrieval layer for your application.
Graph Retrieval
Perseus returns entities, relationships, and traversal paths—not text chunks. Empower your AI to reason over connected structure rather than isolated passages.
An intelligent retrieval pipeline designed for modern AI. By combining semantic search with graph traversal, Perseus ensures your agents always operate on connected, highly accurate data rather than isolated text chunks.
Your agent or RAG pipeline sends a query directly to Perseus, acting as the intelligent retrieval layer for your application.
Perseus executes hybrid retrieval: leveraging graph traversal for deep relational context and vector similarity for precise semantic matching. The results are automatically merged and ranked for relevance.
Your AI receives highly structured context—including named entities, typed relationships, and explicit source references. It can now reason over connected data and respond with grounded, fully traceable answers.
Execute hybrid vector and graph retrieval alongside a robust entity and relation query API. Extract precise subgraphs, configure your retrieval depth, and stream results directly into your agent loops.
Every result comes with explicit source attribution. Guarantee that your AI's responses are not just accurate, but fully auditable—an absolute necessity for operating in regulated domains.
Teams hitting accuracy or traceability ceilings with standard RAG. Agent developers whose AI needs to reason over connected knowledge rather than just searching passages. Regulated-industry teams needing fully auditable answers.
Flat RAG retrieves text that contains the answer. Graph retrieval retrieves the structure that is the answer—the relationships between entities, the path through your domain model, and the source that established each fact. For regulated domains where traceability is mandatory, this is not optional.