Lumiata offers an AI-powered predictive analytics platform that combines diverse health care datasets into unified patient records ready for machine learning. The platform draws on clinical intellectual property and data sources including 120 million patient records, 35,000 physician-curated hours, lab results, billing codes and insurance claims, plus 50 million PubMed articles. Lumiata says it maintains over 100 pretrained models that are 5%–35% more accurate than leading prediction models and can predict more than 20 diseases within 12 months. Its apps can stratify patients for remote care or intervention, anticipate hospitalization and readmission risk, and calculate health care resource needs and associated costs. Deployments are described as low- to no-code, cloud-based, scalable, integrable via APIs, and include autonomous quality checks to keep datasets current. The company raised $14M in a Series B and plans to use the funds to scale the platform, invest in customer acquisition, and open an office in Guadalajara, Mexico in 2021; its total capital raised now exceeds $50M. Lumiata builds AI-powered predictive analytics using clinical knowledge, data science and deep learning for health plans, providers and self-insured employers to manage health costs and risk. The company offers models that predict disease risk and onset of certain chronic conditions and has developed cost and spend prediction models with demonstrated improvement. Since launch it has developed models covering over 20 million patient lives. Led by CEO Dilawar Syed, Lumiata works with major U.S. health plans and providers. The company is based in San Mateo, CA and intends to use the new funding to accelerate development of a new suite of predictive analytics products. Its recent financing brought total funding to $31M. Lumiata offers predictive-analytics products designed to pinpoint individuals at risk for chronic conditions and forecast how those risks change over time. Its core product, Risk Matrix, maps risk trajectories for each member or patient in a population. The company builds on its Lumiata Medical Graph, which it says contains more than 260 million data points, 4TB of structured and unstructured medical knowledge, 35,000 hours of physician review and an expanding repository of over 60 million patient lives drawn from claims, EHRs, labs and sensors. Lumiata reports about 10 paying customers and roughly 10 additional organizations using its technology in proof-of-concept pilots; customers include Independence Blue Cross and partners across payers, accountable care organizations, and digital health companies such as Intellivisit. Competitors cited include Verisk Health, Optum Health, and Inovalon. The company plans to use new funding to grow headcount by about 50% (from ~40 to more than 60), with hires concentrated in product development and data science. Lumiata's predictive analytics platform ingests claims, EHRs and sensor data and constructs a "medical graph" intended to predict what patients may need and when. The company says its algorithms can improve patient intake, triage and discharge workflows and provide more prescriptive information around symptoms, medications, risk factors and diagnoses. For payers, Lumiata's tools aim to surface the medical and financial risks associated with individual patients. The startup positions its product as a way to reduce administrative burden and clinical staff burnout through AI automation. Formed just last year, Lumiata is running pilot projects at several hospital networks, provider groups and health insurance companies. Financially, the company has raised $6 million in the latest Series A tranche and $10 million in total to date. Lumiata develops a medical graph that organizes hundreds of millions of medical data points to produce real-time predictive and prescriptive analytics for symptoms, diagnoses, procedures and medications. Its APIs let providers run anonymized medical records, genetic information or sensor data through the graph to receive hyper-personalized predictions and recommendations at the point of care. The engine is being piloted by major hospital networks and health insurance carriers to inform patient care and improve frontline staff productivity. The company says it has processed over 160 million data points, more than seven million pages from textbooks and journals, over 100 gigabits of public data, and logged more than 20,000 physician hours to validate insights. Lumiata plans to refine and commercialize the medical-graph predictive analytics engine and ultimately leverage the graph to give individuals data to optimize their own health and wellness.

Total raised

$45M

Funding rounds

5

Latest round

Series B

Latest activity

Jan 2021