Everything, answered.

DeepSensi is a Cognitive Medical OS, a verified clinical-intelligence system that reasons through a case like a full hospital consilium. It is not a chatbot. It pairs a specialist agent for every discipline of medicine with cross-vendor verification and a certified safety architecture, so its conclusions are auditable and, uniquely, it refuses to invent an answer.

General models predict the most likely words and can hallucinate confidently. DeepSensi is built the opposite way. Every assertion passes 23 independent verification barriers, and when evidence is insufficient it declares uncertainty and names the single test that resolves it. It is the only medical AI with a formally quantified, SIL-4-grade bound on hallucination.

DeepSensi implements the complete DSS Platinum architecture with a certified worst-case bound of 3.23 × 10⁻⁶ per assertion, meeting the IEC 61508 SIL-4 demand-mode target with roughly a 31 times margin. Its certificate is two-dimensional: Platinum architecture, SIL-4-grade bound.

DeepSensi is engineered for regulatory readiness. It is HIPAA and GDPR compliant, EU AI Act aligned by architecture, with an FDA pre-submission (Q-Sub) engaged. Its core anti-hallucination inventions are patent-pending. Deployment follows each jurisdiction’s clinical-software pathway.

By architecture. Zero personally identifiable information is stored, de-identification happens at source, and every decision is cryptographically sealed and auditable. DeepSensi is privacy-preserving by default, for the individual and for the nation.

DeepSensi is operational. Access is granted through pilots and partnerships across physicians, clinics, insurers, regulators and public-health bodies. Request access via the contact page.

DeepSensi was conceived, engineered and formally validated by Tomasz Jan Gomoła, Founder and Chief Architect of DeepSensi PBC (ORCID 0009-0001-5222-6154), author of the Cognitive Medical OS, the Gomola Framework, and the SIL-4-grade anti-hallucination architecture.

On 301 publicly available NEJM Clinicopathological Conference cases (2014 to 2023), among the hardest diagnoses in medicine, DeepSensi reached 86.0% top-1 and 93.7% top-3 accuracy with a 0.0% missed-critical rate, reported as a development-cohort result. A confirmatory prospective study is designated.

Yes. The Gomola Framework (DeepSensi Standard) is open and royalty-free. Any vendor may certify against it, including competitors. The sole requirement is attribution. A safety standard behind a paywall is not a standard. It is a product.

DeepSensi treats clinicians as scored cognitive partners, not external approvers. When a physician’s verified insight helps a patient elsewhere in the network, an outcome-gated model compensates that contribution, the first formal economic model for clinical expertise inside an AI diagnostic system.

Yes. The top deployment tier is a fully air-gapped hospital node: the complete consilium and the entire safety layer run on premises, with no cloud dependency and no byte leaving the building. A satellite-degraded field mode keeps clinics operational on broken links, from remote practices to humanitarian deployments.

Five ways: time returned by the exosuit; a cryptographic reputation score (GCPS) hardened against gaming; outcome-gated royalties when verified insight helps a patient anywhere in the network; a hypothesis marketplace with cryptographic authorship; and compensated, de-identified research contributions through guilds. Compensation never touches clinical judgment: it is outcome-gated, audit-sealed, and engineered inside anti-kickback limits.

Operational. Version 90 runs in production with infrastructure on four continents. Every capability described on this site exists and runs today; nothing on these pages is a mock-up of a future product.

Twelve patent applications are pending, with twenty-four further applications in preparation, covering the anti-hallucination architecture, consilium orchestration, and the clinical-economy mechanisms. DeepSensi publishes the proof, the standard, and the audit. It does not publish the blueprint.

No. NeuroTokens are a transparent unit of account for cognitive work inside the platform: they meter computational costs and settle physician compensation to a thousandth of a cent. There is no public coin and no speculation. Economics never touch clinical judgment: compensation is outcome-gated, audit-sealed, and engineered inside anti-kickback limits.

DeepSensi’s vocal-biomarker telemetry analyzes properties of speech, such as jitter, shimmer, harmonic noise, and tempo, to screen for early neurological drift, toward conditions such as Parkinson’s disease, long before symptoms demand attention. It runs as a by-product of ordinary, documented care, under the same privacy architecture as everything else.

Every case lives in a temporal health graph that never deletes, only supersedes. A digital twin keeps comparing your expected trajectory with what actually happens; when they diverge, the case reopens itself and your physician receives a retroactive alert, even years after the visit.