South Reno Athletic Club partnered with ASCENDING to replace manual and easily misused check-ins with Guest Vision, a facial-recognition web application built on AWS. The solution delivered faster member entry, stronger membership-use controls, and a practical AI path for a small-to-medium business with limited internal AI engineering capacity.
Background
South Reno Athletic Club (SouthRAC) is Northern Nevada's largest fitness club, supporting more than 1,500 daily active users across a 91,000-square-foot facility. As traffic grew, the club needed a more consistent and secure way to validate member access while minimizing front-desk friction.
SouthRAC's leadership identified facial recognition as a way to modernize operations without adding staff burden. The vision for Guest Vision was a browser-based check-in experience that would be easy for both members and administrators to use and maintain.
The Challenge
SouthRAC needed to adopt AI quickly, but faced practical constraints common to SMB organizations.
- Limited in-house AI/ML expertise and constrained development bandwidth.
- Budget limits that made custom model development and long tuning cycles unrealistic.
- A need for lightweight architecture and straightforward operations, without heavy ongoing overhead.
- Security concerns around unauthorized membership usage and identity validation at entry.
Why ASCENDING
SouthRAC selected ASCENDING for its applied AI delivery experience and AWS specialization. As an AWS Advanced Consulting Partner with implementation depth across machine learning and cloud architecture, ASCENDING provided a practical, cost-aware path from concept to production.
The team focused on a managed-services-first approach to reduce risk, compress delivery time, and avoid overengineering. This helped SouthRAC launch a production-ready solution while preserving flexibility for future enhancements.
The Solution
ASCENDING designed Guest Vision around AWS Rekognition as the primary facial-recognition service, integrated with cloud-native components for reliability and maintainability.
- Built a web-based check-in workflow with frontend and backend services deployed on Amazon EKS.
- Implemented facial recognition with AWS Rekognition, including Multi-Vector capabilities to improve matching reliability.
- Applied configurable similarity thresholds so facial data links to user profiles only when confidence requirements are met.
- Stored structured user and check-in data in Amazon RDS for PostgreSQL for operational reporting and administration.
- Enabled image-processing flow through AWS-managed components to keep the platform lightweight and cost-efficient for ongoing operation.
The Outcome
Guest Vision transformed SouthRAC's member entry flow from a manual checkpoint into a streamlined, AI-assisted process. Staff gained better control over access events, while members experienced faster and more consistent check-ins.
- Reduced barriers to AI adoption by replacing custom model buildout with managed AWS recognition services.
- Lowered development and maintenance effort, with potential overhead reduction of up to 90% compared with building and tuning from scratch.
- Improved flexibility by enabling threshold-based tuning for factors such as pose, brightness, and occlusion to raise image quality and match accuracy.
- Strengthened protection against unauthorized membership use while preserving a user-friendly front-desk experience.
