CORA - a geometric language model

CORA is a conversational retrieval agent built on the GDBS geometric substrate. It answers from a geometric lattice rather than a trained neural network, so its responses are traceable to their source and it does not hallucinate by architecture, not by guardrail.

What it is

A geometric language model: queries are resolved over a geometric retrieval substrate (the GMDBS lattice) with full audit logging, instead of being generated by a large neural network. There is no training run and no inference over learned weights.

Why it matters

• No hallucination by architecture. Answers are retrieved and traceable, not synthesized from learned weights.
• Full audit trail. Every retrieval is logged and reviewable.
• Deterministic substrate. CORA runs on the same geometric system that backs GDBS.

Honest scope

CORA is a retrieval agent over a defined corpus, not a general-purpose generative model. Its strength is traceable, auditable answers within its substrate.

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