
United States · Hospital & health care startup
Connie Health is an AI-enabled Medicare navigation platform founded in 2019 and headquartered in Brookline, Massachusetts.
Funding reportedLast round: Series A
Connie Health is an AI-enabled Medicare navigation platform founded in 2019 and headquartered in Brookline, Massachusetts.
The company focuses on helping older Americans make informed healthcare decisions by combining a technology-driven recommendation engine with support from local licensed agents. Its mission is to empower seniors to live healthier lives while minimizing healthcare costs by identifying optimal Medicare plans and connecting them with suitable doctors. The platform offers complimentary Medicare advisory services, assisting users with enrollment, personalized plan recommendations, and provider matching. Connie Health's AI recommendation engine analyzes individual needs to suggest the best Medicare options, including Medicare Advantage, Medigap, and Prescription Drug plans. The company serves Medicare beneficiaries across several states, including Arizona, Texas, Illinois, Florida, and Puerto Rico, and has grown to support approximately 40,000 users.
Funding, as reported
From Connie Health's own website: 3 founders, 5 on the team.
What they build
Known for
health caremedicare plan costsmedicare plan benefits customizationcommunity-based medicare guidancecommunity trust in healthcaremedicare coverage optionsmedicare plan eligibilitymedicare plan networkscommunity-based servicemedicare plan enrollmentmedicare plan assistancemedicare plan quotesmedicare advantagehospital & health caremedicare plan selection toolsmedicare plan comparison technology
Built with from their website
Yoast SEOGoogle Tag ManagerVisual Website OptimizerAmazon CloudFrontHotjardbtWordPress.orgAWS Trusted AdvisorVtiger CRMTypeScript
Font AwesomeApacheYouTubeCloudflare DNSGoogle WorkspaceTaboolaCloudFlareViewport Meta
Add your raise, your deck and your story, and put Connie Health in front of investors. Or tell us what we have wrong.