Research-first AI governance runtime built on non-neural machine learning.
Elora is a custom Python research platform that uses non-neural machine learning to detect AI behaviour patterns and govern execution through a deterministic proposal-to-commit boundary.
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.
Researching AI behaviour under constrained compute conditions.
Current R&D measures instability, drift, and token-efficiency behaviour in resource-limited runtime settings, then applies bounded intervention methods before commit authorization.
Extending Elora beyond typical inference control-plane skills.
Alongside governance control-plane research, Elora explores how non-neural methods can teach additional operational skills not typically built into AI inference engines, while remaining policy-bounded and auditable.
