LizAI XT Platform

LizAI XT is a next-generation AI-powered platform that transforms fragmented, unstructured clinical data into real-time, structured datasets with exceptional accuracy and speed. It unifies diverse medical data into comprehensive, disease-specific outputs—organized by clinical variables or custom parameters—delivering high accuracy even in complex cases like cancer and COPD, without overfitting. The platform offers real-time data structuring with sub-second retrieval, high performance on minimal hardware, full client-side control to meet strict privacy regulations, and seamless integration with EMR/EHR systems, AWS HealthLake, and Google Vertex AI. Scalable across clinics, hospitals, pharma, and government, LizAI XT enables secure, efficient, and intelligent healthcare data management—unlocking the full potential of AI in medicine.

All-in-One AI-powered Data Operating Platform for Healthcare

A Fully Secured Al-powered Platform for Client-Controlled Healthcare Data Management.

DATA COLLECTION

Step 1 - Idea

Clinical data mega-structures of specific institutions into AI - ready datasets

Healthcare Systems to Data Types

Healthcare Systems

HIS

EHR/EMR

DUR

PAC/RIS

LIS/LABS

APIs

FHIR Files

Lab Results

Imaging

Clinical Notes

Life Logs

Genome

Data Types

EHR IntegrationCerner, Epic, MEDITECH, NextGen, AllScript, AthenaHealth, eClinical Works, AdvanceMD, and more.

Healthcare FHIR DataData is supported by FHIR R4 resources.

Unstructured DataData as different formats, e.g., PDF, txt, imaging, DICOM, etc.

Unstructured DataData in forms of particular schema, e.g. table

DATA MANAGEMENT

Step 2 - Collaboration

Efficient and Accurate Extraction, Structure, and Code of Datasets

Thousands of fragmented files are structured into datasets in one file whose form (table, graph, ete.) can be flexibly designed

DATA INSIGHTS

Step 3 - Planification

Data Insights & Al Development

Precision disease prediction, intervention efficiency, and cost-effectiveness across healthcare levels

Clinically relevant database consists of a total ~115,000 files, across 16 diseases, scattering in different types and formatss

Mega-structured all patients' data per disease by relevant variables, which can be flexibly designed in any forms

Colorectal Cancer
Patient ID	Colon malignancy	Anemia (disorder)	Biopsy of colon	... more variables	Histopathology	MRI
Px01	Yes	No	Sigmoid colon biopsies	...

COPD
Patient ID	Chronic obstructive bronchitis	Pulmonary emphysema	Spirometry	... and 71 more variables
Pz02	Yes	Yes	unknown	...
Px03	No	Yes	Yes	...

Asthma
Patient ID	Childhood asthma	Budesonide	Shortness of Breath	... and 63 more variables
Pt04	Yes	60 ACTUAT budesonide 0.09 MG/ACTUAT Dry Powder Inhaler [Pulmicort]	Yes	...

What to Expect

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• It’s scalable and secure
• Artificial Intelligence Feature
• Offline version available

Qualifications & Requirements

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• It’s scalable and secure
• Artificial Intelligence Feature
• Offline version available