Ambra Cloud Vendor Neutral Archive (Cloud VNA) vs. Kanteron Systems

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Ambra Cloud Vendor Neutral Archive (Cloud VNA)
Score 7.1 out of 10
N/A
Ambra Health headquartered in New York offers a cloud VNA that aims to provide a flexible framework over the internet in which images can be transferred, viewed, and patient imaging and data can be joined together.N/A
Kanteron Systems
Score 0.0 out of 10
Enterprise companies (1,001+ employees)
Patient-centric Enterprise Clinical Content Platform with built-in diagnostic and workflow tools designed to drives continuity of care and reduces care gaps. Integrating clinical data: Medical Imaging (PACS, VNA, RIS), Digital Pathology (WSI, Vendor-neutral Dicomization), Clinical Genomics (NGS), Pharmacogenomics (PGx), and Biosensors. With clinical data, users can: INGEST & STORE On-site or in the cloud INTEGRATE Open source and using standards ANALYZE…N/A
Pricing
Ambra Cloud Vendor Neutral Archive (Cloud VNA)Kanteron Systems
Editions & Modules
No answers on this topic
No answers on this topic
Offerings
Pricing Offerings
Ambra Cloud Vendor Neutral Archive (Cloud VNA)Kanteron Systems
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoYes
Entry-level Setup FeeNo setup feeRequired
Additional Details—Pricing can be either SaaS subscription, one-off license, per usage, even value-based (a percentage of savings or increased productivity).
More Pricing Information
User Testimonials
Ambra Cloud Vendor Neutral Archive (Cloud VNA)Kanteron Systems
ScreenShots

Kanteron Systems Screenshots

Screenshot of Digital Pathology, Vendor-neutral DicomizerScreenshot of Digital Pathology Case ManagementScreenshot of Clinical Genomics with over 15,000 in-silico panels and filters in natural languageScreenshot of Clinical Genomics reporting and annotationScreenshot of Medical Imaging PACS, VNA, and ZFP viewerScreenshot of Flexible Artificial Intelligence / Machine Learning (use your own or any third-party training dataset and algorithms)