Jonda Health offers an AI-powered platform that transforms fragmented healthcare data from various formats into a standardized, interoperable asset. Our solution uses NLP and machine learning to normalize clinical terminology and data structures, enabling healthcare providers and researchers to access and analyze critical information more effectively.
Funding
Funding not disclosed
Founders
Product
Problem
Healthcare data is often fragmented and presented in disparate formats, including PDFs, HL7 messages, and proprietary lab outputs, making it difficult to integrate and analyze. This lack of standardization and interoperability hinders the extraction of actionable insights, impacting clinical decision-making and operational efficiency.
Solution
Jonda Health provides an AI-powered platform designed to transform complex and varied health data into a standardized, usable asset. Our solution ingests data from multiple sources and formats, employing natural language processing (NLP) and machine learning algorithms to normalize terminology, units, and data structures. This process ensures data interoperability, enabling healthcare providers, researchers, and patients to access and interpret critical information more effectively. By harmonizing data, Jonda Health facilitates improved health outcomes and streamlines operational workflows within healthcare systems.
Target Audience
Our primary customers are healthcare providers, including hospitals and clinics, as well as clinical research organizations and laboratories that handle diverse patient data streams.
Features
- AI-driven data ingestion and parsing engine capable of processing diverse formats including PDF, HL7, FHIR, and PNG.
- Proprietary NLP models for semantic understanding and normalization of clinical terminology, units of measure, and data representations.
- Data harmonization pipeline that standardizes disparate data points, such as various notations for white blood cell counts (e.g., "6690-2 Leukocytes," "WBC," "White Cell Count").
- Secure, HIPAA, PDPA, and GDPR compliant data storage and processing infrastructure.
- API for seamless integration with existing Electronic Health Records (EHR) and laboratory information systems (LIS).
- Data visualization tools that present harmonized data in an accessible format for clinical review and research analysis.
- Automated data validation and quality assurance checks to ensure data integrity post-transformation.