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Description
ScienceDesk's data automation simplifies the integration of artificial intelligence within the field of materials science. This tool serves as a practical solution for teams to consistently implement and utilize the latest AI algorithms in their daily workflows. It features customizable attributes, universal identifiers, QR codes, and a robust search engine that connects sample data with experimental results. As a groundbreaking platform, ScienceDesk facilitates collaboration among scientists and engineers, allowing them to engage with and glean insights from their experimental findings. However, the full potential of this resource remains untapped due to the diverse data formats and a reliance on specialists to manually retrieve targeted information. The ScienceDesk research data management system addresses this challenge by merging documentation with data analysis within a thoughtfully designed data structure. Our algorithms empower researchers and scientists, granting them comprehensive command over their data. They can not only exchange datasets but also share their analytical expertise, fostering a more collaborative research environment. Overall, ScienceDesk enhances data accessibility and encourages innovative approaches in scientific investigation.
Description
The purpose of the IA software is to seamlessly gather measurement results straight from the designated testing instrument, present that information to the technician, provide a variety of editing, analysis, and auditing tools, and then transmit the results to the production area or alternative laboratories. Each IA is equipped with a single driver program designed to extract data from any testing device that has an electronic output. Over the past three decades, AcquiData has compiled a comprehensive library of software driver programs suitable for nearly every materials testing instrument currently in operation. Operating within a browser environment, multiple IA programs can function simultaneously on a single PC, allowing different technicians to test various samples at the same time. At the core of the Testream®/CS system lies the Lab Server program, which manages the flow of information into and out of each laboratory within the network. This ensures that all data is processed efficiently and accurately, streamlining the entire testing workflow.
API Access
Has API
API Access
Has API
Integrations
Docker
Elastic Cloud
Flutter
GraphQL
Kubernetes
PostgreSQL
Redis
django CMS
Integrations
Docker
Elastic Cloud
Flutter
GraphQL
Kubernetes
PostgreSQL
Redis
django CMS
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
ScienceDesk
Country
Germany
Website
sciencedesk.net
Vendor Details
Company Name
AcquiData
Website
acquidata.com/our-software-products/introduction-to-testreamcs/
Product Features
LIMS
Audit Trail
Certificates of Analysis
Data Import / Export
Electronic Laboratory Notebook
Inventory Management
Lab Instrument Interface
Reporting & Statistics
Sample Tracking
Specification Management
Workflow Management
Scientific Data Management System (SDMS)
Analytics
Artificial Intelligence (AI)
Audit
Centralized Data Repository
Collaboration
Compliance
Data Security
ELN Integration
LIMS Integration
Workflows
Product Features
Quality Management
Audit Management
Complaint Management
Compliance Management
Corrective and Preventive Actions (CAPA)
Defect Tracking
Document Control
Equipment Management
ISO Standards Management
Maintenance Management
Risk Management
Supplier Quality Control
Training Management
Scientific Data Management System (SDMS)
Analytics
Artificial Intelligence (AI)
Audit
Centralized Data Repository
Collaboration
Compliance
Data Security
ELN Integration
LIMS Integration
Workflows