AI Search Engine
An intent-aware research search layer that gathers evidence through complementary retrieval roles in parallel, fuses candidates around the query, and keeps provenance and partial-failure state visible.
Research questions rarely fit a single representation of knowledge. The system interprets each request and sends it concurrently to the retrieval roles suited to the query, so one unavailable lane does not erase evidence returned by the others.
Results are normalized into a shared evidence set and assembled around the question. Source references travel with the retrieved material through result fusion, preserving a visible route back to the evidence.
Optional curation or synthesis stays bounded by grounded retrieved material. When part of retrieval fails, the response records that state and can return surviving referenced evidence instead of presenting an invented complete answer.