Priver Mind is the software that turns the graph your silicon stores into something useful — a user-owned semantic memory that learns, forgets, and proves where its answers came from. The difference from everything else: it runs first on the devices you control, on the Priver Core platform built for it. The hardware gives it a private place to live; this is what lives there.
Software like this normally lives in someone else's cloud. Priver's runs on the device — which is the whole point of the silicon underneath it.
Most AI treats each request as a blank slate, or leans on a flat log of past prompts. Priver Mind replaces that with a user-specific semantic graph — nodes for what you've said and done, weighted edges for how they relate. It reinforces what you return to, lets the stale decay, and can prepare the right memory before you ask.
None of that would be trustworthy in the cloud. It earns its trust by running on hardware you own: stored and aged by Priver Engram, traversed by GTX-1, sealed behind Core's privacy boundary. The software is the intelligence; the hardware is what makes it private. They're built for each other.
Everything starts from one foundation — a weighted semantic graph that personalizes a model at runtime — then branches into trust, ownership, collective learning, embodiment, and discovery. Each is the subject of a pending patent.
Turns a stream of queries into a weighted semantic graph that personalizes a language model the moment it runs — no retraining. Reinforces recurring patterns, decays idle ones, and predicts your likely next move.
Tags every element with provenance and confidence so any decision traces back to its sources — and sends each claim to verifiers independent of the model: a sandbox, a proof checker, a database, a measurement, a human.
Activity across every app is gathered into one cryptographically-owned graph, sliced into independent partitions you control, and sorted by modality and by four axes — time, place, source, and hardware — across your devices.
Many private memories improve a shared system without anyone surrendering raw data. Each node shares only encrypted, differentially-private signals describing categories of memory — never the content.
The same graph leaves the screen: machines record what they sense as an experiential memory, and a world model — sketched by a language model, then grounded in reality — predicts what happens next before they move.
A surprising inversion: instead of the most common path between two ideas, it fences off the obvious route and seeks the least-obvious viable one — turning the knowledge graph into an engine for novelty and cross-domain discovery.
Priver Mind is not a cloud service you log into. It runs on the silicon and the devices Priver builds — which is exactly what lets it keep the promises above. The software needs the hardware; the hardware is what makes the software trustworthy.
Read top to bottom: the mind runs on the silicon, the silicon lives in the devices. Take any layer away and the privacy promise breaks — which is why Priver builds all three.
Priver Mind is built for Priver silicon. Start with the platform it runs on, or the devices that carry it.