Salus architecture: Snowflake SPCS and AWS

A laboratory security team, or the office that reviews vendors for the jurisdiction, wants one picture of protected health information. The reviewers will ask what the application stores, where the governed record lives, and whether a model keeps a copy after the session ends. The public demonstration is synthetic data. Production laboratory data runs in Snowflake Snowpark Container Services, and AI-assisted features call AWS through Amazon Bedrock.

Reviewers will also ask which company operates the host. JIL Sovereign Technologies, Inc. operates this host. salusagentic.com is part of JIL Sovereign Technologies, Inc., a Delaware corporation. SalusAgentic is a trade name of that company. JIL Sovereign Holdings, LLC (WY) owns the SalusAgentic software. Global Hands, Inc. (TX) gave a grant to JIL Sovereign Holdings, LLC (WY) to build salusagentic.com under its public good initiative. The cost to build SalusAgentic was greater than what Global Hands paid. Global Hands may benefit from the software because it gave Holdings that money. JIL Sovereign Technologies, Inc. (DE) operates salusagentic.com. Holdings owns the rights, maintains the code, provides Level 1 support, and does not operate the code. Global Hands, Inc. does not operate this site. A diagram of the software is not a statement that another company runs the laboratory.

Those are the signs.

Salus runs in Snowflake Snowpark Container Services. AI-assisted features call AWS through Amazon Bedrock. Snowflake and AWS each provide a Business Associate Agreement. PostgreSQL remains a supported deployment dialect. The public demonstration is loaded with synthetic data only.

Salus is three separate planes connected over private networking. The application layer, the API and web tier, is stateless: it holds no protected health information on disk and keeps nothing in a local database. It retrieves data, streams it to the user, and discards it when the session ends. The data plane is Snowflake Snowpark Container Services, where the governed record of accessioning, results, and surveillance lives. The AI layer calls AWS through Amazon Bedrock, kept separate so a model never becomes a place data quietly accumulates.

Separating these planes keeps the audit surface small. Because the application servers store nothing, a compromise of the app tier exposes no patient data, and the compliance question narrows to the data plane, where governance actually belongs.

Two things are worth stating plainly, because a security reviewer will find them. Laboratory data runs in Snowflake Snowpark Container Services, and AI-assisted features call AWS through Amazon Bedrock. Snowflake and AWS each provide a Business Associate Agreement. The public demonstration is a self-contained evaluation environment loaded with synthetic data only, so anyone can explore the product without real patient information. PostgreSQL remains a supported deployment dialect.

Traffic between the application layer, Snowflake, and AWS travels over private connectivity, cloud PrivateLink and VPC endpoints, not the public internet. Protected health information never crosses a public network boundary, and access follows a zero-trust posture: verify every request, grant least privilege, and assume the network is hostile rather than trusting anything inside a perimeter.

Traffic is encrypted in transit with modern TLS, and direct identifiers are encrypted at the field level. Encryption at rest of the whole data store is not claimed by Salus as its own control.

Data isolation is role-based at the database, schema, and table level rather than through per-row filtering. In a production deployment each customer runs in its own isolated database, so one organization cannot query another's data, and inside that database sensitive areas such as billing live in their own schema that only the right roles can reach. A technologist's role sees the operational data it needs and nothing more, without a lab having to author and maintain fragile row-level rules.

That coarse-grained, grant-based model is deliberate: it is easier to reason about, easier to audit, and harder to get subtly wrong than row-level security, while still enforcing separation of duties where it counts.

The data plane runs in Snowflake Snowpark Container Services for enterprise scale, governed sharing, and analytics that run directly on the same data operations use. AI-assisted features call AWS through Amazon Bedrock. Snowflake and AWS each provide a Business Associate Agreement. Building on a modern platform does not mean being trapped on it. Salus ships a zero lock-in export engine that returns your complete data, including audit logs, in open formats, JSON, HL7 FHIR, OMOP, Parquet, and CSV, on demand and without exit fees.

Your laboratory retains full ownership and direct control of all raw and processed data, in your own tenant, under your own governance. Nothing about the license restricts export or migration.