REIMAGING HEALTHCARE WITH CLINICAL AI
FOR PREVENTION, EARLY DIAGNOSIS AND MANAGEMENT OF CARDIOMETABOLIC DISEASE
FOR PREVENTION, EARLY DIAGNOSIS AND MANAGEMENT OF CARDIOMETABOLIC DISEASE
Visolyr® Clinical AI Platform utilizes Agentic Adaptive Intelligence™ to enable proactive prevention, early diagnosis, and personalized treatment plans to alleviate avoidable complications, escalating costs and systemic strain on patients, providers and health systems arising from uncontrolled cardiometabolic disease
For Patients
Delivers personalized, coordinated healthcare experiences to manage conditions, stay engaged, and achieve better health outcomes.
For Providers
Reduces cognitive load and streamlines decisions with real-time, patient-specific insights, delivered directly in workflow to improve efficiency, accuracy, and outcomes.
For Health Systems
Drives financial performance and optimizes utilization for healthcare organizations by proactively identifying high-risk patients, delaying disease progression, and reducing acute care events.
Visolyr is pleased to announce our acceptance into NVIDIA® Inception, a program that nurtures startups revolutionizing industries with technological advancements.
Visolyr® creates dynamic, patient-specific documentation by combining information from multiple sources to deliver concise synopses and highlight actionable insights.
Visolyr® utilizes NVIDIA® Inference Microservices (NIM)™ with TensorRT™ and TensorRT-LLM™pre-optimized inference engines to build upon non-supervised pre-trained LLMs and fine tunes the model with healthcare data to understand and generate domain-specific content while maintaining the general language and reasoning capabilities of the foundational model.
Visolyr® integrates and sequences data, workflows, and AI models based on patient-specific clinical context to deliver precise, timely insights within existing systems.
Visolyr® uses dynamic model selection to automatically choose the most suitable AI model for each task, optimizing accuracy and relevance based on the patient’s clinical context and data type.
Visolyr® streamlines repetitive tasks by generating structured content to prepopulate forms for referrals, prior authorizations and drug therapy enrollment.
Visolyr® leverages NER to extract and classify entities with our generative AI content creation capabilities, resulting in more accurate and contextually relevant responses associated with patient information from disparate sources.
Domain-Specific Adaptation
Adapting pre-trained models to specific healthcare use cases to improve accuracy and relevance
Model Optimization
Fine-tuning models for better performance, faster inferencing and lower resource consumption
Multi-Modal Capabilities
Enhancing generative models to handle multiple types of input (e.g., text, image, video, and audio)
API-enabled Microservices
Ensuring seamless deployment of AI models across various cloud platforms or on-premises environments
Enterprise Integration
Integrating generative AI into legacy systems, CRMs, or ERP platforms
Multi-Cloud Support
Ensuring seamless deployment of AI models across various cloud platforms or on-premises environments
Conversational Interfaces
Designing AI-driven chatbots, voice assistants, or interactive systems for customer service or engagement
Personalization
Building systems that adapt AI outputs based on user preferences and/or previous interactions
Interactive Dashboards
Creating dashboards for visualizing AI outputs and monitoring model performance
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