◆ Gentoo Logic · Modeling Warehouse

Architecture comparison

Hippocratic AI vs Veeva

Hippocratic AI runs closer to the foundational model (Native (own / self-hosted weights)) than Veeva (Cloud-hosted (Bedrock/Vertex/Azure)). No shared foundational model — different bets.

Hippocratic AI

Healthcare

Proximity
Native (own / self-hosted weights)
Models
proprietary / self-built models
Cloud · datastore
AWSproprietary healthcare data lake (details undisclosed)vector database for embeddings and retrieval (inferred)relational/operational DB for tooling and orchestration (inferred)
Compliance
HIPAA (healthcare PHI handling, inferred from domain and clinical deployments)Enterprise security controls on AWS (NVIDIA case study mentions AWS deployment)[5]
Architecture

Hippocratic AI’s production architecture centers on the Polaris constellation: a core healthcare conversation LLM surrounded by 30+ specialized supervisor, verifier, and tool-call models, many built on open-source foundations but trained and operated as proprietary healthcare agents in AWS.[1][3][5][8] The system uses online and offline LLM judges plus task-specific engines (e.g., overdose, labs/vitals, benefits, scheduling) to monitor and govern voice interactions and workflow actions at clinical scale.[1][4][8]

Veeva

Healthcare

Proximity
Cloud-hosted (Bedrock/Vertex/Azure)
Models
middleware / wrappers
Cloud · datastore
AWSOracleown
Compliance
HIPAASOC 2GxP
Architecture

Life-sciences cloud; Veeva AI exposes partner LLMs over regulated CRM/clinical data with a governance layer.

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