HumAIn products
Technology that increases what human networks can do.
We launch products built around a simple premise: the future of AI is not only larger models. It is better relationships between people, information, and action.
What we build
- Network language models
- Trust and provenance infrastructure
- Community intelligence systems
- Institutional memory
- Human/AI coordination tools
- Contribution and attribution systems
Product principles
Human agency stays visible
The system should make it clearer who decided, contributed, approved, or disagreed—not quietly absorb the work into an opaque model.
Context is not just data
People, relationships, history, incentives, and boundaries shape the meaning of information. A useful system preserves that context instead of flattening it.
Contributions should compound
When a person contributes to a network, the value should not evaporate at the end of a session. Products should help useful work become reusable infrastructure.
Provenance is a feature
A system that cannot show where an important claim came from is not finished.
Current direction
The first product experiments explore network language models: systems that treat relationships, pathways, and accumulated context as part of the intelligence substrate.
That does not make a network model automatically better. It makes a different hypothesis testable.