Knowledge
Trusted external sources and community-governed Indigenous knowledge remain distinct, attributable and visible.
SILAC
A community-controlled knowledge environment for Indigenous communicators—focused initially on climate resilience, biodiversity, forests and agriculture.
Process
Local interpretation and validation shape what becomes useful communication and action.
Control
Indigenous knowledge is not silently merged into a training dataset. Provenance and local governance remain intact.
What SILAC is for
SILAC helps Indigenous communicators work with external knowledge without giving up control over their own.
SILAC is designed for contexts where connectivity, devices, language resources, technical support and institutional capacity may all be constrained.
Rather than building an “Indigenous LLM”, SILAC creates a locally controlled knowledge environment in which:
- trusted external knowledge can be searched and interpreted
- community knowledge can remain governed locally
- sources and provenance stay visible
- communicators can compare different knowledge systems
- outputs can be validated before becoming public communication
- the underlying AI model remains replaceable
First implementation
Peru
The first implementation is being developed for Indigenous communicators in Peru, initially around climate resilience, biodiversity, forests and agriculture.
The goal is a practical diálogo de saberes: enabling communicators to draw selectively on global knowledge, compare it with community knowledge and lived experience, and turn that dialogue into locally useful communication while preserving context, provenance and community control.
Built from the environment outward.
SILAC is the first practical expression of the LowRes.AI framework.
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