Clinical intelligence deserves evidence.
Specialized models to understand and structure medical information and link it to its sources.
Clinical understanding technologies built for health systems: precise concepts, preserved context, semantic interoperability and controlled compute costs.
- Label
- type 2 diabetes mellitus
- System
- SNOMED CT
- Code
- 44054006
- Hierarchy
- Clinical finding
1 mention
#1 · page 1 · type 2 diabetes mellitus
0.377 · 0.101 · 0.153 · 0.013
Understand clinical meaning, not just recognize words.
Confirmed, suspected, negated or family history: the same term carries different information.
Clinical extraction
Identify the medical concepts in supported documents.
Contextualization
Distinguish affirmed, negated and hypothetical mentions, and other situations covered by the models.
Terminologies
Map clinical wording to supported reference terminologies, including SNOMED CT.
Multilingual
Link medical expressions across validated languages and terminologies.
Social determinants
Documented social information, structured when the models cover it.
Traceability
Link results to the documents and passages that contributed to their extraction.
From mention to usable informationClinical information keeps its context.
- 3
Deliver
Produce structured results, traceable to their source documents.
- 2
Contextualize
Understand their meaning and map them to shared reference terminologies.
- 1
Identify
Detect medical mentions and concepts in the analyzed content.
Medical memory, built on your existing IT system.
The HL7 feeds already in place populate a FHIR server. CLARYS Medical Memory unlocks their value, for care and beyond.
Secure IT system · on-premises or cloud
Deliver · Care and data
Existing applications
- Admissions
- Radiology
- Laboratory
- X
- Y
- EHR
Application data: logical target
Application data
Standardize · Secure
Standardized data
Read · Connect · Unlock
Primary and secondary value
Contextual call to CLARYS Medical Memory
- Secure external access
- Mobile access
- Community care link
- Single point of access
Only ADT and document feeds, which everyone has mastered for years.
With your usual interoperability partners or your own teams, setup is simple: your existing feeds are all it takes.
Measured performance.
Scale, speed, coverage: CLARYS Intelligence is benchmarked on realistic volumes and against an open-source reference.
At the scale of a healthcare facility
10,000 patients, 100 documents per patient on average
- 120 ms
- response time
- < 2 min
- for full ingestion*
- ÷ 100
- 60 GB of documents reduced to 600 MB after ingestion
Compared with MedCAT, the open-source reference
228 clinical reports, same SNOMED CT and ICD-10 scope
- +33%
- more distinct concepts identified (2,118 vs 1,590)
- ×8
- more ICD-10 concepts recognized (319 vs 39)
- 94%
- of concepts found by MedCAT also detected
- 1.5×
- faster: 8.1 ms vs 12 ms per document
Internal ESPEIR measurements. Deterministic, reproducible extraction, with no generative model. Results specific to the stated corpora and scopes. * Ingestion excluding OCR, on documents already available as text.
Structured data that works with existing systems.
An exchange format is not enough: clinical information must be identified, contextualized and properly represented.
FHIR R4
Standardized resources, depending on available profiles.
International Patient Summary
The patient’s key information, based on available data.
Clinical terminologies
Concepts mapped to the supported coding systems.
Traceability
The origin of every result, always traceable.
Prepare for data reuse without blurring purposes.
Providing care does not automatically authorize reuse: research and management follow their own governance and access rules.
The EHDS in Europe and comparable programs elsewhere are gradually strengthening these frameworks. ESPEIR builds capabilities that support these changes, but cannot by itself guarantee regulatory compliance.
Comparable frameworks, country by country
European Health Data Space
Patient summaries, interoperability and governed reuse of data, with obligations phased in from 2029.
Elektronische Patientenakte
The ePA für alle has been rolling out since 2025. Hospitals upload discharge letters and laboratory and imaging results, among other documents.
Single Patient Record
The NHS 10 Year Health Plan sets out a single patient record, available in the NHS App from 2028.
Rural Health Transformation Program
$50 billion over 2026-2030 to modernize rural care, including data-sharing platforms and clinical networks in which community health centers (CHCs) take part.
Let’s evaluate CLARYS Intelligence on your use case.
Let’s define the concepts you need, the test corpus and the quality criteria your project requires.