Talk With Acuity.
AI can learn your institution. Who owns what it learns?
The next healthcare lock-in is not the software. It is the institutional intelligence created from your workflows, policies, decisions, outcomes and people.
One operating layer built around your population. Intelligence stays yours.
Your patients. Your clinicians. Your institutional intelligence.
Do not trade institutional intelligence for AI access.
A health system can keep its patient data and still lose the intelligence created from that data if the learning accumulates inside a vendor-controlled model, memory or cloud.
Send context out. Rent the intelligence back.
Workflows, overrides, local policies, outcomes and institutional decisions can become durable intelligence outside the institution.
The risk is deeper than data lock-in: the organization may lose control of the learning created by its own care delivery.Keep the intelligence. Share what you choose.
Acuity brings governed computation to the local clinical state, preserves provenance and separates institutional intelligence from platform intelligence.
Participation in network learning is explicit. Private intelligence remains private.Know what belongs to whom.
Federation only works when ownership, provenance and learning rights are explicit before intelligence moves.
Clinical records, patient state and protected health information remain governed by the institution and applicable data rights.
Local workflows, policies, thresholds, calibrations, overrides, outcomes and institutional knowledge remain institution-controlled and portable.
Acuity's clinical-state architecture, Evidence Contracts, CHI, Cue orchestration, governance, provenance and evaluation infrastructure remain Acuity platform IP.
Only explicitly permitted, validated and appropriately generalized learning participates in the federated network.
Compute follows the population.
The institution does not have to send its durable intelligence to a central model. Acuity can run in Acuity cloud, a customer VPC, on-prem or dedicated compute.
Your institution
Only permitted intelligence crosses the boundary.
Shared intelligence
Bring the question to the data.
Federation sends bounded hypotheses, algorithms or evaluation packages to the local environment. Only authorized results leave.
Local clinical data and patient state remain governed at the node.
CyberCue applies identity, purpose, scope and learning permissions.
Models and deterministic logic evaluate locally.
Outcomes and evaluations determine what is trustworthy.
Only permitted generalized learning enters the network.
Federated underneath. Simple at the point of care.
The architecture changes who owns the intelligence—not the clinician's need to know who changed, why and what comes next.
help now?
Illustrative product rendition
Weight increased. Dyspnea appeared. Cardiovascular state worsened.
No hidden intelligence boundary.
The model can change. The cloud can change. The institution's durable intelligence should not disappear with either.
Institution-owned rules, workflows, calibrations, ontology extensions, evaluations and provenance remain exportable rather than trapped inside a model vendor.
Foundation models reason over governed context. They are not the authoritative clinical state or the durable institutional memory.
Identity, tenant, purpose, consent, provenance, learning rights, permitted scope and destination travel with the intelligence.
Organizations can keep intelligence private or explicitly participate in a governed learning network.
Compute can follow the institution's security, latency and sovereignty requirements.
A maintained export can preserve institution-owned state, graph extensions, workflows, calibrations, evaluations and rights metadata.
Institution, Acuity platform and network-derived intelligence remain distinguishable rather than collapsing into one opaque model.
Network learning is based on explicit permissions and validated artifacts—not automatic centralized capture.
Choose how much intelligence leaves.
Architecture and commercial deployment can match the institution's governance posture instead of forcing one centralized model.
Run Acuity against local institutional state with no network learning beyond what the organization explicitly permits.
Participate in governed shared learning while patient data and private institutional intelligence remain local.
Run the clinical intelligence stack inside institution-controlled infrastructure while retaining Acuity's governed platform layer.
The future is not one company owning healthcare's memory. It is healthcare institutions owning their intelligence—and choosing what the network learns together.
One operating layer without surrendering the intelligence your institution creates.
Acuity makes clinical intelligence computable, governable, portable and federatable—while preserving the boundary between institutional intelligence, Acuity platform intelligence and shared network learning.