Behaviour Research
Observer Research Engine
Observer runs bounded investigations into AI behaviour, interventions, runtime conditions, and evidence quality, producing durable records rather than isolated benchmark scores.
Behaviour Research
Observer runs bounded investigations into AI behaviour, interventions, runtime conditions, and evidence quality, producing durable records rather than isolated benchmark scores.
Each run retains its declared purpose, configuration, lifecycle, and evidence so results can be interpreted in context.
Scenarios and research packs define the conditions being studied, while run state records what actually executed and when.
Semantic observations, behaviour signals, threat review, interventions, repairs, and outcomes are retained at the stages where they arose.
Related child runs can be grouped into one logical research job without losing their separate timelines, models, conditions, or outcomes.
Engine manifests and execution evidence make it possible to distinguish configured intent from the components that participated in a run.
Reports can combine run summaries, stage timelines, semantic evidence, Echo observations, interventions, resource effects, and governed outcomes.
Human-readable and structured exports support engineering review, comparison, archival analysis, and future reproducibility work.
Results can be compared across models, scenarios, conditions, and research generations while keeping environment claims appropriately bounded.
Failure, incomplete evidence, and unevaluated states remain visible rather than being collapsed into a favourable result.
Observer can measure, interpret, and recommend. Its findings cannot authorize execution; any consequence-bearing continuation remains subject to the governance and commit boundary.