iCallina Reviews & Product Details

iCallina is a Voice AI Operations Manager solution that helps dental clinics in Spain automate patient communication, schedule appointments, and manage inbound calls. Designed specifically for the dental industry, iCallina provides automated voice assistance in both Castilian, Catalan or 60+ languages, functioning 24 hours a day to ensure all patient inquiries are addressed outside of normal business hours, during midday closures, and on weekends. The software utilizes natural language processing to interact with patients in a conversational format. It integrates directly with clinic calendar systems to autonomously book, modify, or cancel appointments based on real-time availability. Additionally, the system is programmed to recognize dental emergencies, such as acute pain or trauma, and immediately alerts dental staff via automated mobile notifications so urgent cases can be triaged appropriately. iCallina is built to assist administrative teams by gathering necessary patient information during the initial phone interaction. The system captures and records relevant insurance provider details, accommodating major Spanish health insurers to streamline the check-in process upon patient arrival. Clinic managers receive daily automated revenue and call-recovery reports, detailing the volume of calls handled and appointments secured by the system. Core features of iCallina include: Automated 24/7 call answering and conversational voice AI in Castilian and Catalan. Direct calendar integration for patient-led appointment booking and rescheduling. Emergency symptom detection with automated alerts dispatched to clinical staff. Inbound data capture for patient insurance information prior to clinic visits. Daily automated reporting on call volume, appointment metrics, and recovered revenue. Full compliance with the General Data Protection Regulation (GDPR) and the Spanish Data Protection Agency (AEPD). iCallina serves dental practices seeking to reduce missed inbound calls, alleviate administrative workloads for front-desk staff, and standardize their patient scheduling processes