What challenges did FDC Dental face before AI implementation?

Manual, unscalable patient booking caused patient wait times up to one hour and created operational bottlenecks. Manual HR recruitment screening was too slow to meet demand during rapid company growth.

What was the impact of the AI solution?

Reduced patient booking time from one hour to 15 seconds. Enabled HR to screen hundreds of CVs in the time it previously took to process one. Cut infrastructure costs by 35% through serverless auto-scaling. Increased operational scalability to support company growth from 30 to over 100 clinics.

Rank#140of 3,117

Source

GCP

FDC Dental AI Chatbot Booking and HR Screening on Google Cloud

Use case typeAutomotive operations automationUpdated Jun 13, 2026

FDC Dental, a healthcare company in Indonesia, aimed to improve patient booking efficiency and HR recruitment scalability amid rapid expansion. They developed an AI-powered chat-based booking system using Google Cloud technologies including Vertex AI and Gemini models for natural language interaction, Cloud Run for auto-scaling, and Google Kubernetes Engine for infrastructure. The AI chatbot reduced patient booking time from one hour to 15 seconds, enabled automated screening of hundreds of CVs rapidly, and cut infrastructure costs by 35%. The system scales from one agent per clinic to one agent serving 30 clinics, increasing operational efficiency and supporting growth plans.

Organization: FDC Dental
Industry: Healthcare
Location: Indonesia
Published: May 2026

Reported outcomes

−35%

costCost savings

15 secondstime

Strategic outcomes

New product / capabilityLaunched AI-powered chat booking systemSpeed & agilityStreamlined patient booking processScale & capacityEnabled scalable clinic growthNew product / capabilityAutomated high-volume HR screening

Catalog median for cost savings deployments: −45% across 349 reported metrics. Compare benchmarks →

Primary read

Use case focus

Showing 3 of 3

1AI Chatbot Booking
2HR Recruitment Automation
3Operational Scalability

Manual, unscalable patient booking caused patient wait times up to one hour and created operational bottlenecks.
Manual HR recruitment screening was too slow to meet demand during rapid company growth.

Implemented an AI-powered chat-based booking system using Google Cloud Vertex AI and Gemini models to provide natural language conversation and personalized interactions.
Used Cloud Run for serverless auto-scaling to handle demand fluctuations efficiently while reducing infrastructure costs.
Utilized Google Kubernetes Engine for scalable and resilient deployment of AI services.

Technologies

Vertex AI Gemini Cloud Run Google Kubernetes Engine

Reduced patient booking time from one hour to 15 seconds.
Enabled HR to screen hundreds of CVs in the time it previously took to process one.
Cut infrastructure costs by 35% through serverless auto-scaling.
Increased operational scalability to support company growth from 30 to over 100 clinics.

Architecture

Architecture is built on Google Cloud with an AI chatbot using Vertex AI and Gemini models for natural language booking, Cloud Run for automated serverless scaling, and Google Kubernetes Engine for infrastructure management.

Implementation partners1

Tridorian

Sources & evidence1

Groundedness: 5/5

Primary source

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Customer evidence