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CODIFY PROPRIETARY KNOWLEDGE
Driving better outcomes with codified healthcare knowledge
Harness Knowledge Graphs to decode deeper insights, enhance AI accuracy, improve clinical decision & patient outcomes
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CODIFY PROPRIETARY KNOWLEDGE
Smarter healthcare AI with Knowledge Graphs
Healthcare data is often fragmented across systems, making it difficult to extract meaningful insights. To stay ahead, organizations must transform unstructured knowledge into machine-readable intelligence. Codify proprietary knowledge to enable seamless data integration, and improved decision-making using Generative AI and Knowledge Graphs.
Enterprise Knowledge Search
Recommendations
Clinical Decision Support
Personalized member experience
Patient Prioritization
Pharmacovigilance
Document Collection & Data Ingestion
Aggregating structured & unstructured data from multiple sources.
Entity Extraction & Resolution
Identifying and linking
entities accurately using LLMs.
Relation
Extraction
Structuring data with standardized ontologies for consistency.
Knowledge Graph
Creation
Use the entities, relationships and domain schema to create knowledge graphs.
Querying & Insights Generation
Enable pattern recognition and real-time insight extraction from knowledge graphs.
Accelerating adoption and scaling with GenAI-powered knowledge graphs
Prebuilt solutions
Collaborative development
Scalable platforms
Ready to unlock the potential of your Healthcare intelligence?
OUTCOMES
Elevating performance for better healthcare delivery
Connect structured
& unstructured data
Explainable AI
& predictable outcomes
Vector embedding
support
Grounded,
fact-based AI
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Fine-grained access
control (RBAC)
Use Case
Intelligent search & recommendations
Enhance clinical workflows and patient experiences with smart search and recommendation systems powered by Generative AI and knowledge graphs. Enable physicians, care teams, and even patients to quickly access relevant clinical guidelines, similar case histories, treatment pathways, and medical literature tailored to context, thereby improving speed and accuracy in decision-making.
Use Case
Codification of care process maps
Digitize and standardize complex care pathways by converting them into structured, machine-readable formats using knowledge engineering. This supports better adherence to clinical protocols, enables automation opportunities, and allows seamless integration with CDS systems, reducing care variability and improving outcomes.
Use Case
Reimagining Claims with knowledge graphs
Leverage AI and semantic models to analyze large volumes of claims data to identify patterns, uncover care gaps, flag fraud or abuse, and inform value-based care strategies. Create a unified view that connects clinical, operational, and financial dimensions for more informed payer-provider collaboration.
Use Case
Smarter policy management
Transform static, complex policy documents into dynamic, queryable knowledge graphs. This enables real-time understanding of benefit rules, enhanced policy version control, and regulatory compliance, thereby enhancing automation in document processing and decision support while reducing administrative burden.
