Vitaspan provides an AI‑driven platform that ingests fragmented medical records from EHRs, labs, clinics and insurers, cleanses and normalises the data, and maps it to clinical taxonomies. The structured, AI‑ready data powers real‑time predictive insights and health alerts, enabling clinicians to identify risks earlier and intervene proactively. By automating data integration, Vitaspan reduces the time clinicians spend on information management and supports personalized, preventive care.
Funding
Funding not disclosed
Founders
Product
Problem
Clinicians spend a large portion of their time reconciling fragmented medical records from multiple sources such as EHRs, labs, clinics, and insurers, which delays diagnosis and limits proactive care. This data silos hinder early detection of chronic, preventable diseases and increase overall healthcare costs.
Solution
Vitaspan provides an AI‑driven platform that ingests, cleanses, and normalises patient data from disparate health systems into a single, structured dataset. The unified data is mapped to clinical taxonomies and enriched with machine‑learning models that generate real‑time health alerts and personalized care recommendations. By delivering predictive insights directly to clinicians and patients, the platform enables earlier risk identification and proactive intervention. The solution integrates with existing EHRs, laboratory information systems, and insurer databases, allowing seamless adoption without replacing current workflows. Structured, AI‑ready data also supports downstream analytics such as risk stratification and population health management, improving outcomes while reducing costs.
Target Audience
Primary customers are healthcare providers and health systems that need consolidated patient data for clinical decision support, as well as insurers and health‑tech platforms seeking structured, AI‑ready datasets for risk assessment and population health initiatives.
Features
- Automated ingestion pipelines for EHRs, labs, clinics, and insurers with secure, HIPAA‑compliant data transfer
- Data cleansing and normalisation engine that maps raw records to standardized clinical taxonomies (e.g., SNOMED, LOINC)
- Predictive analytics layer that produces real‑time health alerts and individualized care plans based on AI models
- Clinician dashboard delivering actionable insights, risk scores, and trend visualisations within existing workflows
- API and FHIR‑compatible interfaces for integration with third‑party health applications and analytics tools