Knowledge Retrieval

What it is

Enterprise RAG, Graph RAG, ontology-guided retrieval, hybrid search, evidence retrieval and hierarchical retrieval architectures, with citation and provenance systems that make every answer checkable.

Why it matters

Retrieval quality decides whether an AI system is trustworthy. A retrieval layer that ignores structure returns plausible fragments. One that uses the ontology, the graph and the provenance chain returns evidence an expert can verify.

How AeonBridge approaches it

AeonBridge builds retrieval over the knowledge infrastructure: chunking invariants measured rather than assumed, per-organisation isolation verified by mutation testing, a groundedness gate that removes unsupported sentences, and per-claim citations that resolve to the source span. Retrieval is evaluated with harnesses, not demos.

Outcomes

• Answers with verifiable citations
• Enterprise search that respects boundaries
• Measurable retrieval quality