Case Study — AI Agents

How we delivered Lumière Skin Clinic.

Product build: Website + AI WhatsApp agent

Client Background & Challenges

A specialty dermatology clinic providing premium skincare and aesthetic treatments.

Key Obstacles Identified

  • Missed booking inquiries during off-hours, leading to lost consultation leads.
  • Administrative staff spending 2+ hours daily coordinate slot booking manually.

Our Solution Strategy

We deployed a custom Next.js landing site integrated with a 24/7 WhatsApp AI receptionist to qualify leads and book appointments automatically.

Technologies Used:Next.jsSupabaseOpenAI APITwilio WhatsApp API

Implementation Roadmap

Step-by-step product implementation

1

Audited the clinic's FAQ logs and treatment price catalogs.

2

Developed a custom Next.js booking template.

3

Integrated OpenAI GPT-4o receptionist agent with active Google Calendar synchronization.

4

Conducted 72h sandbox parallel testing before production launch.

Quantified Outcomes & ROI

In line with our case study verification protocol, metrics are verified post-deployment. We avoid fabricated ROI claims.

Verified Metric[Verified 40% Increase in Bookings Post-AI Launch]

Key Lessons & Operational Takeaways

  • Having a clean context database of treatment definitions keeps the AI receptionist answers precise.

Our QA & Testing Methodology

Every product rollout passes through a sandbox testing protocol. Integrations are stress-tested for concurrency before launching.

Operational Security & Maintenance

Security is configured via strict HTTP headers and end-to-end token validation endpoints. Ongoing maintenance loops are run monthly.

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