Payers
Expand high-value membership segments, drive operational efficiency, and improve medical cost management through predictive analytics and AI agents.
Expand high-value membership segments, drive operational efficiency, and improve medical cost management through predictive analytics and AI agents.
Invene traced recurring data failures to their source, corrected brittle third-party integration patterns, and defined a technical roadmap to reduce long-term dependence on external vendors.
Invene built an AI-driven platform and a full design system with coded components to deliver insights across web, native, and wearables.
Invene designed the Patient Health Forecast and DS workbench that won CMS’s AI Health Outcomes Challenge and Best in KLAS.
Invene transitioned their whole on-prem software application, including their reporting modules, to the cloud on Microsoft Azure.
Invene architected a scalable Enterprise Data Warehouse, integrated fragmented data sources into a unified structure, using data fabric principles to streamline analytics and decision-making.
Invene developed a quoting automation system that streamlined bid generation through intelligent workflows, reducing manual effort while optimizing cost structures and consolidating platform dependencies.
Invene implemented an automated data extraction process that leveraged authenticated sessions and intelligent automation, ensuring seamless and reliable data aggregation for real-time insights.
Invene designed a whole new architecture and deployment process for a critical system with millions of claims transactions a day.
Invene predicted health outcomes for low socioeconomic populations based on few-shot data.
Working closely with Community Health Options’ team, Invene improved accounts receivables processes that effect tens of thousands of their members.
Tackling the Hardest Software & Product Problems in Healthcare
