NTL HEALTHCARE unveils on-premises AI cervical screening

Estimated reading time: 5 minutes · Last updated: 18 October 2026

NTL HEALTHCARE has launched CerviCARE® AI AT, an on‑premises version of its CerviCARE AI cervical screening system that runs on local PCs and reduces reliance on external cloud services. The product is the same CerviCARE AI clinical engine repackaged to let institutions perform image analysis and manage associated files inside their own IT environments. The company says the on‑premises option joins the existing SaaS offering, giving healthcare organisations a choice between the two deployment options and adding DICOM file generation for standardized storage.

As global adoption of medical AI continues to grow, healthcare institutions are placing increasing importance not only on AI performance but also on how medical data is processed and managed within their own IT environments,

Tae-hee Kim, CEO of NTL HEALTHCARE

What CerviCARE® AI AT is and how it differs from the SaaS product

CerviCARE® AI AT is the on‑premises edition of CerviCARE AI, NTL HEALTHCARE’s image‑analysis system for cervical screening. Instead of routing images to a vendor cloud, institutions install the software on local personal computers; NTL presents this as an alternative to the vendor’s SaaS service. The clinical algorithms and core analysis features are reported to be the same as the SaaS version, so hospitals that need to retain data locally can run the same screening workflows without sending images outside their IT environment.

NTL HEALTHCARE positions the launch as an expansion of deployment choices rather than a separate product line; organisations that prefer cloud operation can continue with the SaaS offering, while those with strict data governance can select the on‑premises package.

How the on‑premises architecture changes data handling

The vendor describes CerviCARE® AI AT as installable on local PCs and able to operate without a dedicated server or cloud infrastructure, which reduces the need to transmit images beyond the institution. Running the analysis and data management inside an organisation’s own network gives IT teams direct control over storage, backups and any local security controls they already apply to other clinical applications.

Keeping image files in‑house can simplify compliance with institutional policies that restrict outbound transfers of medical images, and it removes one layer of third‑party custody. That said, shifting responsibility to local IT also means hospitals must provision endpoints, secure desktops, and maintain software updates for every deployment point.

DICOM support and clinical workflow integration

A headline technical addition in the on‑premises release is DICOM file generation for cervical images and related metadata. DICOM, the industry standard for medical imaging, lets images be archived and retrieved by hospital picture‑archiving systems in a consistent format; the company says CerviCARE® AI AT can convert screening images into that standard for storage and management.

Standardized file output can ease integration with local imaging archives and some clinical workflows, but it does not by itself guarantee plug‑and‑play operation with every hospital system. Local integration work—mapping metadata, assigning patient identifiers and testing retrieval—will typically be required before the AI output is used in routine screening pathways.

What this means for adopters and for NTL HEALTHCARE

For healthcare institutions, the new deployment option narrows the tradeoff between using an advanced AI screening engine and maintaining tight control of medical images. Facilities that were hesitant to use cloud‑hosted AI because of data residency or policy constraints now have an on‑site option that runs the same analytic core.

For NTL HEALTHCARE, offering both SaaS and on‑premises releases is a distribution strategy that addresses different IT environments and procurement preferences. The company’s CEO, Tae‑hee Kim, framed the launch as a response to growing concern about how medical data is processed and managed inside institutional systems.

What could move this either way

The bottom line

NTL HEALTHCARE’s CerviCARE® AI AT formalises an option many hospitals have sought: run AI screening locally while retaining standard image output. The change answers data‑residency and policy concerns by moving analysis and file handling inside an organisation’s own IT perimeter and by adding DICOM export for archiving. Adoption will hinge on hospitals’ willingness to take on endpoint management and integration work; until vendors or early adopters publish case studies or technical guides, IT teams should factor validation, security and support into procurement decisions.

What to watch

• Watch for NTL HEALTHCARE announcements about partner hospitals publishing deployment or local‑validation summaries; no date has been set.
• Watch for NTL HEALTHCARE to publish further technical integration guides or supported‑systems lists; no date has been set.
• Watch for case studies showing how CerviCARE® AI AT’s DICOM export is used with local imaging archives; no date has been set.

This article is information, not medical advice. Anyone acting on it should speak to a qualified professional.