Eric Pinet, president of Qu\u00e9bec City-based Unicorne, shares insights on the challenges of transitioning AI from demo to real-world deployment. The key issues include managing cost, security, and compliance. AI prototypes often stall between promise and deployment, with costs becoming unsustainable at scale and security concerns arising from reliance on external APIs. Unicorne’s approach prioritizes infrastructure management to meet compliance standards, particularly in regulated environments. Their health-tech project in Qu\u00e9bec, which involves a voice-based AI for triaging patient calls, demonstrates the importance of integrating AI within existing workflows without compromising data security. Pinet emphasizes the need for founders to address practical questions about production systems early on to ensure successful deployment.<\/p>\n","protected":false},"excerpt":{"rendered":"
Eric Pinet, president of Qu\u00e9bec City-based Unicorne, shares insights on the challenges of transitioning AI from demo to real-world deployment. The key issues include managing cost, security, and compliance. AI…<\/p>\n","protected":false},"author":1,"featured_media":951,"comment_status":"","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[1434],"tags":[9816,18049,413,2002,18048],"class_list":["post-14585","post","type-post","status-publish","format-standard","has-post-thumbnail","category-global","tag-ai-deployment","tag-cost-management","tag-global-startup-news","tag-health-tech","tag-security-compliance"],"acf":[],"yoast_head":"\n