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Our platform is meticulously crafted with a focus on regulatory compliance, enhancing the landscape of clinical research by employing advanced algorithms to analyze unstructured EMR data for the identification of critical health conditions. We are at the forefront of innovation, developing state-of-the-art technologies that expand access to transformative healthcare solutions through Clinical Trials. Our passionate team is driven by a mission to save lives by improving access to therapeutic advancements still under investigation. We firmly believe that every patient deserves to be informed and empowered about their options to participate in clinical trials that may provide substantial therapeutic advantages. As a progressive healthcare AI research organization, we have developed a sophisticated computational platform that accurately identifies patients who fulfill an extensive range of criteria necessary for participation in clinical trials, ensuring that those best suited are prioritized for these vital studies. Ultimately, our goal is to transform the way patients discover and engage with potentially life-altering treatment options, fostering a new era of healthcare possibilities. Through these efforts, we aspire to bridge the gap between innovative research and patient access, making a tangible difference in the healthcare landscape.
What is BeeKeeperAI?
BeeKeeperAI™ utilizes state-of-the-art, privacy-focused analytics across various institutions' secure data within a protected computing environment that incorporates comprehensive end-to-end encryption, secure enclaves, and advanced SGX-enabled processors from Intel to safeguard both data integrity and the intellectual property of its algorithms. By keeping data confined to the organization's secure cloud infrastructure, it significantly reduces risks related to loss of control and the likelihood of data being improperly shared. The platform utilizes authentic data directly obtained from original sources, steering clear of the disadvantages associated with synthetic or anonymized datasets, and ensures that all information remains consistently encrypted. It is equipped with specialized tools and workflows designed specifically for healthcare applications, which enhance the processes involved in dataset creation, labeling, segmentation, and annotation. Moreover, the secure enclaves provided by BeeKeeperAI™ successfully neutralize risks of data theft and unauthorized access to algorithmic intellectual property, protecting against threats from both internal and external sources. Functioning as a bridge between data holders and algorithm developers, BeeKeeperAI™ simplifies data projects, achieving reductions of over 50% in time, effort, and costs incurred. This pioneering model not only bolsters security measures but also encourages cooperative efforts within the data science community. Additionally, the platform's emphasis on privacy protection fosters greater trust among stakeholders, promoting a more robust data-sharing ecosystem.
Integrations Supported
MySQL
SQL
API Availability
Has API
API Availability
Has API
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Pricing Information
Pricing not provided.
Free Trial Offered?
Free Version
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Supported Platforms
SaaS
Android
iPhone
iPad
Windows
Mac
On-Prem
Chromebook
Linux
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Company Facts
Organization Name
Dyania Health
Date Founded
2019
Company Location
United States
Company Website
dyaniahealth.com
Company Facts
Organization Name
BeeKeeperAI
Date Founded
2021
Company Location
United States
Company Website
www.beekeeperai.com/solution
Categories and Features
Natural Language Processing
Co-Reference Resolution
In-Database Text Analytics
Named Entity Recognition
Natural Language Generation (NLG)
Open Source Integrations
Parsing
Part-of-Speech Tagging
Sentence Segmentation
Stemming/Lemmatization
Tokenization
