Products
DocuSense.ai (Document Analysis and Management):
Global Alliant's experience in data management, especially in large-scale case management and information access, can support DocuSense.ai in organizing and analyzing document-driven insights. Their work with the National Labor Relations Board’s Judicial Case Management System and other secure portals highlights Global Alliant's capability in handling complex document workflows and optimizing document storage, retrieval, and access for secure and efficient data management.
National Labor Relations Board (NLRB) Case Management System: Global Alliant managed over 200,000+ judicial case records with functionalities supporting search optimization, indexing, and automated retrieval. They also successfully migrated data to a new platform with minimal downtime, ensuring consistent access to critical records.
Health Resources and Services Administration (HRSA) Verification & Validation (V&V) Project: In testing grants systems, Global Alliant's automation reduced manual testing by 70%, saving approximately 1,000+ person-hours annually. This efficiency can be applied to DocuSense.ai to streamline document validation and minimize manual intervention.
Flow.ai (Workflow Automation):
Global Alliant's role in automating virtual machine provisioning, database management, and case management showcases their capability in streamlining workflows and managing automated systems. Their automation experience with the NLRB and other government projects can aid in enhancing Flow.ai’s automation capabilities, creating a smoother, faster, and more reliable workflow engine for various industries.
NLRB VM Provisioning Automation: Global Alliant's team automated the deployment of virtual machines, which resulted in a 50% reduction in provisioning time, cutting the average setup from 2 hours to under 1 hour. Such efficiencies in Flow.ai can similarly improve overall workflow timelines, particularly for complex task sequences.
Washington Suburban Sanitary Commission (WSSC): During the migration of billing systems to Oracle C2M, Global Alliant's automated several customer service workflows, improving response times by 30% and reducing service costs by 20%. These workflow automation strategies are directly applicable to Flow.ai’s aim for streamlined, cost-effective processes.
FHIR (Fast Healthcare Interoperability Resources):
Global Alliant's projects with the Centers for Medicare & Medicaid Services (CMS) and Health Resources and Services Administration (HRSA) demonstrate their expertise in healthcare data integration, testing, and secure data handling. This experience is directly relevant for FHIR, where secure and efficient health data exchange is crucial. Global Alliant background with medical platforms and compliance standards will help ensure FHIR integration meets rigorous security and interoperability requirements.
Centers for Medicare & Medicaid Services (CMS) Data Integration: In the CMMI Innovation Support Platform project, Global Alliant managed secure data access across 3,000+ unique healthcare models and ensured real-time access for evaluation and reporting. Their platform for CMS supported over 100,000 data transactions daily and involved strict data handling and encryption protocols, directly aligning with FHIR’s need for secure, scalable data exchange.
Health Resources and Services Administration (HRSA): Global Alliant's automation of grant application testing for HRSA reduced deployment time for updates by 40%. These efficiencies can improve FHIR implementations by automating data validation across healthcare applications.
AI-ML (Artificial Intelligence and Machine Learning):
Global Alliant has demonstrated experience in analytics and reporting for CMS and other federal agencies, which supports AI/ML needs in predictive analytics, data-driven insights, and model lifecycle management. Their expertise in data migration, analytics, and model validation/testing will provide a strong foundation for any AI/ML initiatives, ensuring accuracy, efficiency, and data integrity in model development and deployment.
Predictive Analytics for CMS: Global Alliant's analytics work with CMS involved processing millions of healthcare data points to track and forecast outcomes, essential for developing AI models. This experience is applicable to any AI/ML platform requiring rigorous testing and validation for model accuracy.
Automated Regression Testing: Global Alliant implemented automated regression testing frameworks for HRSA and CMS, which increased testing coverage by 30% and reduced testing cycles by 50%, ensuring reliable, data-driven insights essential for machine learning and AI model lifecycle management.
