Memory your agents can prove they relied on.

Sapere is the governance layer between your organization's knowledge and the AI agents acting on it. It combines a governed memory graph, action governance on the write path, and a tamper-evident audit you can replay — so an agent can act on what your organization actually knows, and you can prove what it relied on.

A vector store gives you similarity search over text; Sapere gives you governed memory. Facts carry provenance, decisions are bitemporal, writes are vetted before they count, and every grounded action is recorded in an audit you can replay. It is the part that turns retrieval into something you can trust and defend.

Two things. On the way in, the write path vets every proposed fact and fails closed, so unproven knowledge stays quarantined until it is promoted through a role-gated path. On the way out, grounding records the exact memory an agent used, and a hash-chained audit makes that record tamper-evident. Governance is enforced by the engine, not by convention.

Grounding is an agent drawing on real memory before it answers or acts — with the precise set it relied on captured. Replay re-checks that captured state later and tells you whether it is verified (unchanged), revised (the world moved on), or tampered. It is how a grounded action stays auditable long after it happened.

Yes. The autonomy dial lets an operator tune how much autonomy an agent has earned on a given lane — confidence and agreement thresholds — and publish it as a versioned policy. The engine enforces safety floors that can be tightened but never widened away, so more autonomy is always a deliberate, recorded decision.

No. Sapere is its own product with its own console, identity, and data plane. It shares Prodedify single sign-on, but its memory and audit live independently — you can adopt Sapere on its own to govern your agents, whether or not you use anything else in the stack.