How Affidea automated three patient journeys with Axendi AI voicebot

An introduction

Healthcare organizations manage thousands of patient interactions every day. Many of them—appointment booking, examination confirmations, reminders, and post-visit surveys—follow predictable processes that are essential for delivering a positive patient experience, yet require significant operational effort. 

Rather than introducing AI as a one-time transformation, Affidea adopted a gradual approach. Over time, Axendi Primebot was implemented across multiple patient communication processes, each addressing a specific operational challenge and reducing the volume of repetitive interactions handled by agents. 

The objective was never to replace people. It was to automate routine conversations, optimize operations, and allow customer service teams to focus on interactions where human judgment, empathy, and personalized support create the greatest value.   

The challenge

Healthcare providers must balance two competing priorities: delivering a positive patient experience while using administrative resources efficiently. 

Many patient interactions follow predictable, standardized processes. Booking examinations, confirming appointments, and collecting patient feedback are all essential, yet they account for a considerable share of daily workload. 

Rather than increasing headcount to manage growing demand, Affidea sought to optimize these processes by introducing AI voicebots where automation could deliver the greatest operational value.

The objective was not to replace agents, but to reduce repetitive work and enable teams to focus on interactions requiring empathy, problem-solving, and individual support. 

• Standardization of repeatable patient communication processes  
• Phased implementation of AI Voicebots across selected patient journeys  
• Optimization of operational capacity through intelligent automation 

The solution

Primebot Platform. Three patient journeys.

Appointment booking

Appointment booking for MRI and CT examinations required agents to handle thousands of routine interactions, limiting their availability for patients who needed more complex support. 

Voicebot 

• collects information 
• creates reservation 
• transfers difficult cases 
• available 24/7 

Results 

• 920,948 booking processes 
• 121,235 completed booking confirmations 
• 11,000+ hours automated 
• 1380 working days saved (since 10.2022)

Appointment confirmation 

Registration teams spent hundreds of hours confirming examinations. 

Voicebot

• confirms attendance 
• provides preparation instructions 
• handles cancellations 
• handles rescheduling.

Results

• 25,000 conversations every month 
• 13,000 confirmed appointments 
• 460 hours automated every month 
• 58 working days saved (01.-06.2026)

Patient survey

Surveys needed to be delivered at the right time, completed by a sufficient number of patients, and translated into actionable operational insights. 

Voicebot

• conducts NPS survey  
• sends invitation to Google review 
• generates data that supports patient experience analysis.

Results 

• 124,000+ surveys 
• 81 NPS 
• 85.5% promoters 
• 10,000 hours automated 
• 1300 working days saved (since 2023)

The human + AI model

Technology automates repetitive, structured conversations. People focus on interactions that require judgment, empathy, and problem-solving. The outcome is better use of agents’ expertise. This principle underpins all three AI implementations. 

Operational impact of implementing Axendi AI voicebot 

• 1,000,000+ patient conversations automated 
• 21,000+ hours of conversations automated 
• 2,700+ working days released 
• 124,000+ patient satisfaction surveys 
• 25,000 appointment confirmations every month 
• 24/7 patient availability 

  

Optimizing operations through intelligent automation

Affidea’s AI strategy was based on a simple principle: automate processes—not expertise.  

A human-centered approach to AI implementation

Affidea’s AI strategy was based on a simple principle: automate processes—not expertise. 

Rather than treating AI as a standalone technology project, the organization introduced Voicebots progressively, identifying patient communication processes where automation could deliver measurable operational value. Each implementation addressed a different stage of the patient journey, while following the same operating philosophy. 

Instead of asking which conversations could simply be transferred to a Voicebot, Affidea evaluated which interactions genuinely required human expertise and which followed predictable, repeatable workflows. 

Routine patient communication was automated to reduce administrative workload, while consultants continued to manage conversations requiring empathy, judgment, problem-solving, and individualized support. 

Over time, this approach created a consistent patient communication model across multiple touchpoints. Supported by the Axendi team, Affidea improved operational efficiency, increased service availability, and delivered a smoother patient experience—without changing the role of consultants, but by changing how their expertise was used.