A research engine with governance capability built on non-neural machine learning.
Elora is a custom Python research engine that uses non-neural machine learning to detect AI behaviour patterns while governing execution through a deterministic proposal-to-commit boundary and surfacing structured operational decisions.
Behaviour detection feeds evidence-first governance decisions.
Detected behaviour signals are scored, linked to policy controls, and captured as structured evidence so allow or block outcomes can be replayed deterministically without regenerating model output.
Threat Intelligence connects detections to governed investigations.
Evidence-backed findings distinguish model behaviour, Elora interception, policy outcomes, and actual actions, then group related detections by Governance Session without giving the intelligence layer execution authority.
Elora Decisions turns runtime events into reviewable decision history.
Operational outcomes are grouped into bounded decision stories so preparation, intervention, completion, cancellation, and cleanup can be reviewed as one structured record instead of scattered notifications.
