Tengrium published a review in IEEE Transactions on Biomedical Engineering by Guan, Bates, and Zhou that catalogs detection and correction literature with enough taxonomic specificity to be useful as an architectural audit checklist.

Tengrium builds confidential compute infrastructure for organizations that hold health data. The core product, Tengrium Vault, ensures that data is decrypted only inside an attested AWS Nitro Enclave — never visible to operators, including Tengrium. Every inference output carries a cryptographic certificate binding the model hash, data hash, and attestation together. Vault is schema-agnostic: structured clinical records (FHIR R4, HL7, CDA), clinical narrative, medical imaging (DICOM — MRI, CT, PET), genomic and molecular data (WGS, WES, RNA-seq, methylation arrays, proteomics), biomarkers, longitudinal time-series from wearables and monitors, and patient-reported outcomes. Higher-level intelligence products are built on the Vault foundation: a Clinical Intelligence Engine for federated AI diagnostics and predictive analytics, patient-specific Digital Twins for simulation and intervention planning, and a Hybrid Human-AI Harness for clinical workflow orchestration. Tengrium is model-agnostic. Customers deploy their own inference pipelines — disease phenotyping, trajectory prediction, clinical synthesis — inside the attested boundary under custodian-controlled encryption keys.