NINJIO is an all-in-one cybersecurity awareness training solution that lowers human-based cybersecurity risk through engaging training, personalized testing, and insightful reporting. This multi-pronged approach to training focuses on the latest attack vectors to build employee knowledge and the behavioral science behind human engineering to sharpen users’ intuition. Our proprietary NINJIO Risk Algorithm™ identifies users’ social engineering vulnerabilities based on phishing simulation data and informs content delivery to provide a personalized experience that changes individual behavior.
With NINJIO you get:
- NINJIO AWARE attack vector-based training that engages viewers with Hollywood style, micro learning episodes based on real hacks.
- NINJIO PHISH3D simulated phishing identifies the specific social engineering tricks most likely to fool users in your organization.
- NINJIO SENSE is our new behavioral science-based training course that shows employees what it “feels like” when hackers are trying to manipulate them.
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Docmosis is a self-hosted or SaaS template-based document generation solution. Integrate with custom-built software applications or popular third-party apps using the API.
Create templates using MS Word or LibreOffice. Add plain-text placeholders to control: the insertion of text/images/tables; conditionally add/remove any content; perform calculations; loop over repeating data; format data/numbers and much more.
Integrate with: Custom software built using Java, C#, Python, PHP, Ruby and more via a REST API; Low-code and no-code platforms like Appian, Bubble, Mendix, Outsystems; Third-party form builders or apps that can perform a webhook such as FormAssembly or Salesforce.
Used by customers in Finance, Health, Legal, Education, Government, HR, Insurance, Logistics, and Manufacturing to generate customized letters invoices, proposals, contracts, statements, reports and more.
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Verana Health
Verana Health operates as a platform for real-world data that converts both structured and unstructured information from electronic health records into curated, de-identified, disease-focused data modules through its clinician-informed and AI-enhanced VeraQ population health data engine. By aggregating data from key collaborations with prominent medical registries, including the American Academies of Ophthalmology, Neurology, and Urological Association, the platform integrates insights from over 20,000 clinicians and approximately 90 million patient records, thereby supplying high-quality datasets in near real-time for the purposes of generating real-world evidence, identifying clinical trial sites and subjects, reporting clinician quality, and managing medical registries. Users can access this wealth of information through cloud services like AWS Data Exchange and Amazon Redshift, which provide self-service API access, a user-friendly dashboard, and tools for customizable cohort discovery. Furthermore, the system employs advanced AI and machine learning algorithms along with comprehensive data quality assessments to ensure the reliability and accuracy of the information provided. This innovative approach not only facilitates efficient data utilization but also enhances the overall quality of healthcare research and practice.
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Clinical Extract
Clinical Extract is capable of retrieving research information from any electronic health record system equipped with a certified bulk FHIR API, including platforms like Epic, Oracle Health (Cerner), athenahealth, eClinicalWorks, MEDITECH, NextGen, and Veradigm. This tool operates within your own infrastructure as a SMART Backend Services client, utilizing read-only permissions, and facilitates the export of only the designated study group via a Group $export, transforming NDJSON into a comprehensive CSV complete with a data dictionary that identifies the FHIR element corresponding to each column. Importantly, patient information remains securely within your environment. Designed specifically for cancer and clinical registries, it accommodates coded case and abstraction fields in accordance with the NAACCR layout, as well as meeting the needs of research informatics teams and honest brokers by providing study-specific pulls paired with an IRB-compliant data dictionary, and assisting research sites with clinical trial feasibility assessments based on coded criteria. Among its notable features are a cohort builder, roster extraction using FHIR $match, the generation of the CSV and data dictionary, and a specialized oncology perspective that presents biomarkers and TNM stage as clearly labeled columns, ensuring ease of analysis. This comprehensive approach enhances the accessibility and usability of critical health data for various research applications.
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