Technology
AI applied to radiology, with the specialist at the center.
Our architecture combines language models, medical knowledge retrieval and human review. The goal is to accelerate the radiologist — never replace them.
Supervised AI
Every AI output is designed to be reviewed and approved by a specialist before it becomes a clinical product.
Medical Agentic RAG
Knowledge retrieval on curated radiology corpora with agents that reason over clinical context.
Portuguese clinical NLP
Medical language understanding in pt-BR, structured radiology terminology and modality-aware mapping.
Model orchestration
Task-specialized LLMs combined: dictation, structuring, terminology suggestion and review.
Production infrastructure
Scalable cloud architecture with a focus on low latency, availability and observability.
Privacy & LGPD
Per-tenant isolation, clinical data governance and LGPD principles from design.
Engineering principles
- AI as a copilot: real report speed, physician in control.
- Terminology precision before generic fluency.
- Clinical safety and privacy as requirements, not features.
- Fast iteration with real radiologist users.