Patient Data Is Everywhere.
It's Already Degraded by the Time It Matters.
A single patient's record is not a record. It is a scattered set of identifiers, files, images, labs, notes, prescriptions, and encounters distributed across hospitals, clinics, labs, and specialty systems. The data exists. The patient exists. But the computational boundary required to unify them safely does not.
Existing approaches force an impossible tradeoff: either move raw data and violate trust, or preserve privacy and lose the ability to resolve identity, compute across sources, and produce clinically meaningful outputs.
A single patient's clinical identity is scattered across hospitals, labs, wellness platforms, pharmacies, and specialty clinics — each with its own schema, its own medical record number, and no obligation to reconcile with anyone else.
Existing systems store encounters. They do not reconstruct the patient.
HIPAA prevents raw-data sharing. De-identification strips the identifiers required to link the same patient across sources. Consent infrastructure between wellness and clinical systems does not exist.
The more private the data becomes, the less computable the patient becomes.
Lab results are clinical-grade at the point of origin — CLIA-certified, CAP-accredited, identical to what hospitals order. The moment that data crosses an institutional boundary into a wellness app, a third-party system, or even a patient portal, chain of custody breaks and provenance becomes unverifiable.
The data doesn't become inaccurate. It becomes institutionally unusable.
Hospitals operate on HL7, FHIR R4, and DICOM. Wellness platforms store proprietary JSON, app databases, and PDFs. Between them sits no standardized translation layer, no shared consent model, and no common trust framework.
Two ecosystems generating the same data about the same patient, unable to exchange it.
Homomorphic encryption is too slow for clinical workloads. Multi-party computation cannot resolve identity across sources. Federated learning leaks gradients and never unifies the record. Policy-based access controls can be overridden, revoked, or breached.
They solve fragments of the problem. None of them solve the full clinical computation boundary.
Provenance That Survives the Journey
Data is intercepted at the point of origin — directly from the CLIA-certified lab — and sealed inside an attested enclave with a cryptographic verification certificate. Provenance is a physical property, not a policy promise. It cannot be stripped downstream.
A Computational Boundary That Didn't Exist
Inside hardware-isolated enclaves, patient identifiers from multiple sources become visible for the first and only time. Identity resolution, record unification, and clinical inference happen in encrypted memory that no party — including Tengrium — can inspect.
Cross-Source Intelligence Without Exposure
Multi-modal AI models reason across clinical, molecular, and genomic data from multiple sources inside the enclave. The vault produces cross-domain clinical insights that no single source could generate alone — without any party seeing another's data.
Complete Clinical Intelligence.
Zero Data Exposure.
Data custodians never see proprietary models. Model operators never see raw patient data. Both meet only inside a hardware-isolated enclave.
Each data custodian encrypts patient records with their own CMK before anything leaves their network. Clinical, genomic, imaging — every modality sealed at origin. Tengrium never sees plaintext.
Inside the enclave, patient identifiers link the same individual across every contributing source — hospitals, laboratories, wellness platforms, biobanks. Identifiers are only visible in hardware-isolated memory.
Multi-model pipelines execute on the unified patient profile — disease phenotyping, progression forecasting, clinical synthesis, pharmacogenomics. Models run on data they can never extract. k-anonymity enforced.
Every computation produces an ECDSA-P256 signed certificate with AWS Nitro attestation, model hash, input Merkle root, and privacy parameters. Independently auditable.
Any structured format · Each source encrypted under its own CMK · AES-256-GCM
Any structured format · Each source encrypted under its own CMK · AES-256-GCM
decrypt(sources[]) // N sources, any modality
patients = resolve_identities(sources[])
phenotype = disease_model(biomarkers) // subtype + stage
trajectory = progression_model(features) // 12/24/36-month forecast
narrative = clinical_llm(unified_profile) // risk + PGx + narrative
cert = sign(results, attestation_doc)
ECDSA-P256 certificate + Nitro attestation · k-anonymity enforced
✓ Mathematically provable: raw data never left the enclave
Quantum-Safe by Design.
Not Retrofitted Later.
Attestation-Gated Keys
KMS only releases decryption keys when the enclave's code hash (PCR0) matches the expected value. Modified code = no keys = no data.
2-Layer Encryption
Customer CMK wraps a data encryption key, which encrypts via AES-256-GCM. Each layer requires separate attestation. Defense in depth by design.
Hardware Isolation
Nitro Enclaves run in a separate VM with no persistent storage, no network, and no interactive access. Even the host EC2 instance cannot inspect enclave memory.
Verification Certificates
Every computation outputs an ECDSA-P256 signed certificate containing model hash, input Merkle root, output hash, and the full AWS Nitro attestation document.
Quantum-Safe Transit & Signatures
All service calls use hybrid PQ-TLS (ML-KEM + ECDH) — quantum-resistant key exchange today. AES-256-GCM at rest is inherently post-quantum. ML-DSA (NIST Level 3) certificate signing on the roadmap.
The Only Approach That Scales
| Tengrium (TEE) | Homomorphic Encryption |
Multi-Party Computation |
Federated Learning |
|
|---|---|---|---|---|
| GPU Acceleration | ✓ NVIDIA CC | ✗ CPU only | ✗ CPU only | ✓ Local GPU |
| Performance Overhead | < 5% | 10,000×+ | 100–1,000× | Network bound |
| Cross-Source Linking | ✓ Inside enclave | ✗ Impractical | ✗ Complex MPC | ✗ Not possible |
| General Computation | ✓ Any AI model | ✗ Limited ops | ✗ Custom circuits | ✗ Training only |
| Verifiable Output | ✓ HW attestation | ✗ No standard | ~ Partial | ✗ No guarantee |
As NVIDIA extends confidential computing to H100 and beyond,
TEE-based approaches are the only privacy model that benefits from GPU acceleration.
Every Modality. Every Marker.
One Unified Clinical Picture.
Inside the enclave, multi-modal models process clinical, molecular, and genomic data in sequence — each layer building on the last — to produce cross-domain reasoning no single data source could achieve alone.
Disease Phenotyping
Simultaneously identifies which progression subtype a patient belongs to and their current stage on a disease timeline — using imaging biomarkers, fluid analytes, and motor scores across multiple validated cohorts.
Progression Forecasting
Builds patient similarity graphs across clinical and genetic features, then propagates information between clinically similar patients to predict motor and functional trajectories at 12, 24, and 36 months.
Attending-Quality Narrative
A clinical language model synthesises all upstream model outputs together with the full multi-modal patient record — producing a risk tier, pharmacogenomic safety flags, and an attending-quality clinical narrative.
"The referring neurologist saw a patient with mild REM sleep disorder and some anosmia. The vault saw a patient 12 months from a Parkinson's diagnosis — with SAA-confirmed alpha-synuclein pathology, the smallest putamen in the cohort, and a dual amyloid-synuclein co-pathology flag that no single-source system would have surfaced."
Seven Modalities.
One Unified Record.
Each patient profile combines data types that have never before been unified — across institutions that have never shared data — without any institution seeing any other's records.
Schema to Inference.
End to End.
Multi-modal patient profiles — EHR, genomics, imaging, transcriptomics — unified inside a single enclave and fed through chained clinical AI. Working today on AWS Nitro.
Who This Is For
Your Users Hit a Ceiling. We Remove It.
Today your users get insights they can't act on. Their doctor won't touch data from an app. With Tengrium, lab results become clinically portable — your platform transforms from a wellness tool into genuine health infrastructure.
- Zero integration cost — we sit between your lab partner and your dashboard
- Clinical data portability as a premium feature your competitors can't match
- From "informational use only" to "clinically portable" — a verifiable property, not a marketing claim
Stop Re-Running Tests Your Patients Already Paid For.
Patients arrive with screenshots from apps. You re-order the same tests because you can't verify what they're showing you. With Tengrium, you receive FHIR-compliant results with attestation certificates proving provenance. Act on them immediately.
- Attestation certificates prove which lab produced the result, when, and that it was never altered
- Results arrive as FHIR R4 DiagnosticReport resources — ready for EHR import
- 21st Century Cures Act compliant — information blocking is illegal, and now it's unnecessary
One Test, Usable Everywhere.
You pay $500/year for wellness labs your doctor won't touch. You end up paying twice — once for the wellness test, again when the hospital re-runs it. Tengrium makes that obsolete.
- Your lab results carry cryptographic proof of origin
- Send attested data directly to any provider you choose
- Full consent control — you decide who sees what, and you can revoke at any time
Multi-Site Evidence Without Moving Data.
Run AI models across distributed hospital data for real-world evidence, cohort identification, and drug safety — without any patient record leaving its source institution.
- Blind inference inside enclaves — the model comes to the data
- Verification certificates prove correct execution across sites
- Clinical trial eligibility flagging from unified multi-source profiles
Your Work Product Deserves Better.
You produce clinical-grade results. The moment they enter a wellness app, the provenance is destroyed. Tengrium preserves the chain of custody from your instrument to the patient's physician.
- Attestation seals results at the point of origin — before downstream degradation
- Your CLIA certification and CAP accreditation travel with the data
- Clinicians receive your results, not a screenshot of an app dashboard
Live In Production.
Now Onboarding Select Partners.
Tengrium is currently available to a select group of healthcare and life sciences organizations. Get in touch below to schedule a private walkthrough of the platform running against a live 100-patient clinical dataset — end to end, inside the enclave.
The future of healthcare won't be incremental.
It will be architected.
Tengrium is building the infrastructure to unify patient data, clinical intelligence, and privacy-preserving computation into a single platform.
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