Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Enhance your scientific research and equip your R&D team with unified data in the cloud. The Tetra R&D Data Cloud merges the only cloud-native data platform specifically designed for global pharmaceutical enterprises with the expansive and rapidly growing network of Life Sciences integrations and extensive industry expertise, providing a robust solution for leveraging your most critical asset: R&D data. This platform encompasses the entire life-cycle of your R&D data, facilitating processes from acquisition to harmonization, engineering, and subsequent analysis while offering native compatibility with cutting-edge data science tools. It supports a vendor-agnostic approach with pre-existing integrations that allow seamless connectivity to instruments, analytics and informatics applications, as well as ELN/LIMS and CRO/CDMOs. By consolidating data acquisition, management, harmonization, integration/engineering, and data science enablement into one comprehensive platform, it simplifies the complexities of R&D operations. This holistic approach not only streamlines workflows but also unlocks new possibilities for innovation and discovery.
Description
ZSegment is an innovative cloud-native interface engine developed by 314e Corporation, tailored to effortlessly link and unify clinical, financial, and administrative systems within healthcare organizations. With an impressive array of over 300 components, it facilitates real-time metrics grounded in open telemetry standards and is built on a Kubernetes-native framework utilizing Apache Camel to provide scalability, adaptability, and user-friendly customization options including version control (Git) and native custom schema support for HL7 v2, FHIR, X12, and CCD. Additionally, it boasts visual tools for message routing, Groovy scripting for data transformations, and secure message delivery through various protocols such as File, FTP, HTTP(S), and TCP. The platform also includes features like message indexing, tracing, editing/resubmission capabilities, and the ability to define custom jobs for data hygiene and operational oversight. As a modern alternative to traditional on-premise interface engines like Mirth Connect, ZSegment helps organizations reduce hardware procurement expenses and high licensing fees, making it a cost-effective solution for enhancing interoperability in healthcare systems. Furthermore, its cloud-native design means that organizations can quickly adapt to evolving demands without the constraints of legacy infrastructure.
API Access
Has API
No
API Access
Has API
No
Integrations
Apache Camel
No
Apache Groovy
No
BIOVIA
Yes
Egnyte
Yes
Git
No
Kubernetes
No
Mirth Connect
No
Tableau
Yes
Integrations
Apache Camel
Yes
Apache Groovy
Yes
BIOVIA
No
Egnyte
No
Git
Yes
Kubernetes
Yes
Mirth Connect
Yes
Tableau
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Pricing Details
No price information available.
Free Trial
No
Free Version
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Deployment
Web-Based
Yes
On-Premises
No
iPhone App
No
iPad App
No
Android App
No
Windows
No
Mac
No
Linux
No
Chromebook
No
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Customer Support
Business Hours
Yes
Live Rep (24/7)
No
Online Support
Yes
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Types of Training
Training Docs
Yes
Webinars
Yes
Live Training (Online)
Yes
In Person
No
Vendor Details
Company Name
TetraScience
Founded
2014
Country
United States
Website
www.tetrascience.com
Vendor Details
Company Name
314e Corporation
Founded
2004
Country
United States
Website
www.314e.com/zsegment/
Product Features
Data Management
Customer Data
No
Data Analysis
No
Data Capture
No
Data Integration
No
Data Migration
No
Data Quality Control
No
Data Security
No
Information Governance
No
Master Data Management
No
Match & Merge
No
Data Science
Access Control
No
Advanced Modeling
No
Audit Logs
No
Data Discovery
No
Data Ingestion
No
Data Preparation
No
Data Visualization
No
Model Deployment
No
Reports
No