Free text, locked in
The hospital’s richest information lives in paragraphs no SQL query can read.
Latrikos turns unstructured clinical information into longitudinal, multicentre and auditable databases, ready for Real-World Evidence, clinical registries and clinical trials.
Clinical AI in real time
A visit, an examination, a report. Clinical practice already produces the data research needs every day — and Latrikos asks it to change nothing.
The doctor writes what they see: diagnoses, treatments, progress. All of it correct, all of it useful — and all of it trapped in prose no database can read.
Building a study means re-reading everything and keying it into Excel or RedCap by hand. Months of work, projects delayed and variables lost along the way.
Drop the reports in exactly as they are. No templates, no integrations and no change to the hospital's workflow.
Every sentence is read in its clinical context and turned into variables traceable to the exact line they came from, with 99% accuracy.
Ready cohorts, comparable variables and results that compute themselves: ten times faster and at 80% less cost.
Multicentre studies on a shared standard, where every site contributes its data without giving up control. Real-world evidence, finally at scale.
Every report written in your hospital holds valuable variables trapped in free text. Latrikos frees them in real time and keeps them ordered, traceable and ready to query — without changing clinical practice.
Four bottlenecks that repeat across every department, and that no record template has ever solved.

The hospital’s richest information lives in paragraphs no SQL query can read.
Structuring records by hand consumes the time of clinicians, data managers and residents.
What gets transcribed is a biased fraction; the rest never reaches any analysis.
Every study starts months late because the dataset has to be built from scratch.
From the raw document to the published study, with no manual exports in between.

From reports, notes or test results, the AI identifies every clinical variable instantly, with its context and its source.
Variables settle into a consistent schema that grows with every document and audits back to the original text.
Define cohorts, launch multicentre studies and follow the evidence in real time, with no manual exports.
A single panel showing processed volume, variable coverage and the status of every active cohort.
Measured across departments that have already structured their full history with Latrikos.
faster to assemble a research dataset
of clinical variables correctly structured
of manual entry time returned to the clinical team
Evaluated on a real clinical corpus against manual extraction, rule-based systems and generic NLP.

They activate research and turn their clinical information into a reusable asset, keeping control and sovereignty.
They launch multicentre registries with a shared model and real-time visibility by site and cohort.
They generate evidence and support clinical development, market access, post-authorisation follow-up and international expansion.
They cut manual work in capture, review, monitoring and database preparation.
Latrikos is built on the European principles for trustworthy AI. They are not a statement of intent: each one maps to a concrete technical decision.
Human-in-the-loop: the researcher co-designs the variables, validates before and after, and checks every result against the anonymised source text.
Continuous validation, SAST/DAST audits and ENS compliance. Access control, traceability, backups and incident management.
ENS · Basic levelDe-identification and pseudonymisation up front. Original documents are deleted after processing: only structured variables persist.
Privacy by designEvery variable keeps a reference to the anonymised fragment it came from. Full traceability and a verifiable result.
The tool does not classify or decide about people. It only structures clinical information that already exists.
Secondary reuse of clinical data on energy-efficient infrastructure.
Energy managementDocumented governance, defined roles and auditing of access and operations across the full processing cycle.
Proactive training for the research team. AI amplifies their work, it does not replace it.
Magnifica HumanitasLatrikos neither makes nor intervenes in clinical decisions: it structures existing information for research purposes.
Low-risk categoryWe only ask for what we need to prepare the first conversation. We design the project together — you do not have to bring it solved.
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