Extensible AI engine connector framework.
Structured contextualization at the canonical-identifier layer. Hypothesis pivots traverse signature, artefact, and behavioral entry modes without re-baselining; intel enrichment binds to the same identifiers analysts query.
Audit-ready evidence as a property of the deployed system. Coverage and gap are continuous, not periodic; supervisory inspections receive structured lineage records aligned with control frameworks (ISO 27001, POJK, BSSN sectoral, UU PDP).
AI capability is a moving frontier. The platform must extend its AI surface without architectural disruption. Plugger is the connector framework that admits new AI engines under contractual integration to Mega Lake.
Plugger exposes engine contracts — input schema, output schema, governance binding. New engines plug into Mega Lake under the contract, inheriting governance and producing identifier-bound output.
New AI engines extend platform reach without rewrite.
Before: AI integrations were bespoke.
Plugged engines inherit lake governance.
Before: integrations bypassed governance.
The platform admits future AI advances under contract.
Before: AI advances stalled at integration.
"Plugger integration connector untuk AI Engine untuk pengolahan informasi berbasis kecerdasan buatan."
— NOGTUS Platform Specification