Lilac provides a cloud‑native analytics platform that automates data aggregation, cleansing, and normalization for health insurers. The modular solution delivers actionable insights for star ratings, risk adjustment, compliance reporting, and member health outcomes. By streamlining data workflows, it helps payers improve profitability and member care.
Funding
$25K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
HAFounders
Product
Problem
Health payers and value‑based care organizations face fragmented clinical and claims data, extensive regulatory reporting requirements, and limited predictive insight, making it difficult to translate abundant quality data into actionable improvements in member health and plan profitability.
Solution
Lilac provides a cloud‑native analytics platform that automates data aggregation, cleansing, and normalization across claims, enrollment, and clinical sources. The platform delivers AI‑driven predictive models that identify emerging quality performance risks and high‑impact care gaps early in the measurement cycle. Integrated workflows enable automated outreach and engagement at scale, turning insights into concrete actions for members. By unifying clinical and financial metrics, Lilac helps payers streamline compliance reporting, reduce manual effort, and improve star ratings, HEDIS scores, and overall plan profitability. The solution is modular and extensible, allowing organizations to add new data sources, AI use cases, and cloud technologies as needs evolve.
Target Audience
Primary customers are health insurers, Medicare Advantage plans, ACOs, and risk‑bearing provider groups that need to manage quality performance, regulatory reporting, and member outcomes at scale.
Features
- Automated end‑to‑end data pipeline that ingests, cleanses, and normalizes claims, enrollment, and provider EMR data in a cloud environment
- AI/ML predictive analytics that forecast star performance, HEDIS outcomes, and other value‑based metrics before gaps widen
- Integrated care‑gap identification and prioritization engine linking clinical and financial indicators
- Scalable, AI‑enabled patient outreach modules for automated engagement and data collection
- Compliance reporting automation for STAR, RADV, HEDIS, and other regulatory requirements
- Modular architecture supporting easy addition of new data sources, analytics models, and cloud services