Our Solutions
Patient Summaries you can trust, without the extra work
Transforming raw, fragmented medical data into structured, interoperable, and reusable health information. Ready for care, research, and innovation.
Patient Summaries –The core of clinical data
A patient summary is a concise, clinically relevant document that provides an overview of a patient’s key medical information. It typically includes core elements such as active problems, medications, allergies, procedures, vaccinations, and recent lab results. The goal is to ensure that any healthcare professional — at any time or place — can quickly understand a patient’s health status and history.
A foundational asset within EHDS and international health strategies
The Patient Summary is increasingly recognised as a key asset in health data strategies — enabling structured, shareable, and reusable medical information across systems and borders.
It can be expressed using international standards such as:
A strategic asset worth maintaining
Maintaining a high-quality, up-to-date patient summary is critical for:
Smart Patient Summary Management
Creating and maintaining high-quality patient summaries is complex. They must unify diverse clinical data — from diagnoses to medications — across specialties and care settings.Our system automates this process, reducing manual effort and errors, while giving clinicians a reliable, structured view of each patient.
Initial content migration
AI-driven transformation of historical medical data
We use AI to automatically extract key clinical concepts from unstructured legacy documentation, capturing both medical meaning and metadata. This information is then mapped to standards like SNOMED CT and LOINC and unified to produce fully structured, coded Patient Summaries — compliant with HL7 FHIR IPS and ready for clinical use, interoperability, and secondary applications
Proven Methodology with Built-In Quality Control
Our proven methodology combines AI-driven quality control with targeted human review to ensure accuracy and clinical relevance — without manual validation of every record.With over 5 million records processed, it’s a scalable, field-tested approach for local to national deployments.
Maintaining the Patient Summaries
Continuously updating the patient summary
As a patient’s health evolves, new clinical data is generated — by different providers, at different times, and across disconnected systems. In this decentralised reality, there’s no single source of truth. Instead, accurate patient summaries must be continuously reconstructed from fragmented inputs.
Relying on clinicians to manage this manually is not sustainable — it’s time-consuming, technically complex, and adds unnecessary burden to their workflow.
Smart AI Capture Flow
In many cases, the most accurate and complete patient data comes directly from the clinician. But asking them to structure data manually is rarely sustainable.
That’s why we’ve developed Smart AI Capture technologies — designed to capture structured information at the point of care with minimal friction and added burden.
AI Transformation Flow
While clinician-entered data can be ideal, it’s not always feasible or desirable. Workflows differ, and a large part of patient information is generated outside the hospital and in unstructured formats — from clinical notes to external reports, labs, or referrals.
Our AI Transformation Flow continuously processes and extracts relevant information from diverse sources including hospital records, external providers (e.g. GPs, specialists, other hospitals), and across various data types such as clinical notes, reports, lab
AI Assisted Consolidation of new records
Consolidating a patient summary is complex — it requires detecting duplicates, grouping similar entries, and updating existing records without losing context. Our AI solutions support clinicians in making the right decisions at the right time, helping improve the consistency, clarity, and overall quality of the patient summary.
- Add new records extracted in the patient documentation
- Update existing records based on new information
- Merge records that refers to the same medical fact
- Consolidating updates into the patient summary in a coherent, duplicate-free manner
Discover the Patient Explorer App
Consolidating a patient summary is complex — it requires detecting duplicates, grouping similar entries, and updating existing records without losing context. Our AI solutions support clinicians in making the right decisions at the right time, helping improve the consistency, clarity, and overall quality of the patient summary.
- Add new records extracted in the patient documentation
- Update existing records based on new information
- Merge records that refers to the same medical fact
- Consolidating updates into the patient summary in a coherent, duplicate-free manner