Language models

Medical LLM with source, limits and human review

Language models in healthcare require control of source, context, privacy and validation before entering any sensitive routine.

Medical LLM for documents, protocols, summaries, agents, clinical RAG, audit, validation, sources and limits of use in healthcare.

01

Possible uses

Protocols, documents, summaries and audit

LLMs can support document search, synthesis, text standardization, coherence checking and the creation of interfaces for institutional knowledge.

02

Hallucination, weak sourcing and incomplete context

Validation before use in a sensitive routine

Validation should measure consistency, source quality, response when evidence is lacking, behavior in ambiguous situations and the risk of misuse.

03

Secure architecture

RAG, logs, access control and review

The architecture must separate sensitive data, retrieved context, system instructions, logs, user roles and human decision.

Innovation & Intelligence

Strategic intelligence for healthcare. From complexity to clarity.

For workflows with sensitive data, we apply minimization and de-identification before any processing by language models, under double data anonymization. We use AI providers via the OpenAI and Google Gemini APIs under enterprise terms, with ZDR (Zero Data Retention) and BAA (Business Associate Agreement) enabled for eligible endpoints.

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AI with clinical responsibility · B2B-only model