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Novoflow is an AI company building AI employees that automate medical operations for clinics. It addresses the problem of missed patient calls and inefficient old reception models by integrating AI-driven voice agents with legacy EHR systems to manage scheduling and reduce revenue loss due to no-shows and missed appointments.<\/p>\n<\/p><\/div>\n<\/details>\n\nHow does Novoflow’s AI receptionist improve clinic revenue?<\/summary>\n\n
By answering every inbound and outbound call, booking and rescheduling appointments directly in any EHR system, Novoflow reduces missed physician hours that cause average monthly revenue losses of $50,000 per clinic, thus reclaiming lost revenue through improved appointment management and increased provider utilization.<\/p>\n<\/p><\/div>\n<\/details>\n\nWhat are the key features of Novoflow’s AI receptionist?<\/summary>\n\n
Key features include 24\/7 multilingual voice AI capable of real-time intent classification, insurance verification, native integration with any EHR system, quick one-hour deployment without new hardware or coding, and a dashboard tracking metrics like call abandonment, conversion, and no-show rates.<\/p>\n<\/p><\/div>\n<\/details>\n\nHow does Novoflow integrate with existing EHR systems?<\/summary>\n\n
Novoflow uses a universal EHR interface compatible with major platforms such as Epic, Athena, Medent, and legacy HL7 feeds, allowing real-time appointment management directly inside these systems without complex code or infrastructure changes.<\/p>\n<\/p><\/div>\n<\/details>\n\nWhat languages does Novoflow support to facilitate patient communication?<\/summary>\n\n
Novoflow’s voice AI supports more than 25 languages, enabling clinics to communicate effectively with diverse patient populations, including those who previously faced language barriers during after-hours calls.<\/p>\n<\/p><\/div>\n<\/details>\n\nWhat measurable benefits have early adopters seen with Novoflow?<\/summary>\n\n
Early adopters reported a 10% increase in provider utilization and a 22% boost in call-to-appointment conversion rates, alongside improved patient satisfaction due to faster, clearer communication and fewer missed calls or appointments.<\/p>\n<\/p><\/div>\n<\/details>\n\nWhat is the deployment process and timeline for implementing Novoflow?<\/summary>\n\n
Deployment involves pointing the clinic\u2019s existing phone number to Novoflow\u2019s SIP trunk, enabling a seamless setup with no new equipment or coding. The entire go-live process takes about one hour, allowing rapid implementation.<\/p>\n<\/p><\/div>\n<\/details>\n\nWhat inspired the founders to develop this AI healthcare receptionist?<\/summary>\n\n
Founders Mathieu and Georges, former medical interpreters, experienced firsthand how language barriers and after-hours call handling failures caused delayed care and revenue loss at clinics, leading them to build a voice AI system integrated with EHRs to solve this bottleneck.<\/p>\n<\/p><\/div>\n<\/details>\n\nHow does Novoflow enhance patient experience?<\/summary>\n\n
Novoflow’s AI receptionist offers personalized, multilingual support 24\/7, reduces wait times by instantly attending calls, verifies insurance in real-time, and handles appointment tasks efficiently, resulting in higher patient convenience and satisfaction.<\/p>\n<\/p><\/div>\n<\/details>\n\nWhat future features is Novoflow looking to test or implement?<\/summary>\n\n
Novoflow plans to beta-test outbound recall automation to proactively contact patients, as well as balance-due collection, further automating and streamlining clinic revenue cycle and patient engagement management.<\/p>\n<\/p><\/div>\n<\/details><\/div>\n<\/section>\n","protected":false},"excerpt":{"rendered":"
Many medical clinics in the U.S. have trouble answering patient calls and face missed appointments. Recent studies show that about 42% of patient calls are not answered by traditional receptionists, call centers, or old phone systems. This leads to clinics losing around $50,000 a month because doctors\u2019 time is wasted and appointments are missed. These […]<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[],"tags":[],"class_list":["post-119745","post","type-post","status-publish","format-standard","hentry"],"acf":[],"aioseo_notices":[],"_links":{"self":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/posts\/119745","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/comments?post=119745"}],"version-history":[{"count":0,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/posts\/119745\/revisions"}],"wp:attachment":[{"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/media?parent=119745"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/categories?post=119745"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.simbo.ai\/blog\/wp-json\/wp\/v2\/tags?post=119745"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}