Avahitech.com is now Avahi.ai
Contact Us

Walla Enhances Member Retention with AI-Driven Churn Prediction on AWS

Client

Walla Software, Inc

Location

San Diego, CA

Industry

Fitness Software / SaaS

Services & Tech

Amazon S3, Amazon EC2, Amazon SageMaker, AWS Lambda, Amazon CloudWatch, Amazon API Gateway, Amazon RDS Postgres, Amazon Glue, Amazon Bedrock, Amazon Step Functions, AWS IAM

Project Overview

Walla Software partnered with Avahi to improve member retention for its fitness studio management platform. The goal was to transition from a prototype churn model to a production-ready solution powered by AWS SageMaker. Avahi implemented a scalable MLOps architecture including automated training, inference, and explainability pipelines. As a result, Walla now has real-time churn predictions with clear insights into why a member might drop out, helping studio owners act proactively.

About the
Customer

Walla Software, Inc. is a SaaS provider based in San Diego, CA, serving boutique fitness studios specializing in yoga and pilates. Their platform offers scheduling, billing, staff coordination, and member engagement tools tailored for studio operators. Walla focuses on simplifying operations to drive client satisfaction and business growth.

The
Problem

Walla Software, Inc. is a SaaS provider based in San Diego, CA, serving boutique fitness studios specializing in yoga and pilates. Their platform offers scheduling, billing, staff coordination, and member engagement tools tailored for studio operators. Walla focuses on simplifying operations to drive client satisfaction and business growth.

Why AWS

Walla selected AWS for its scalable machine learning capabilities, managed infrastructure, and integration flexibility. Amazon SageMaker offered a fully managed service to orchestrate training, retraining, and inference at scale. AWS also provided access to services like CloudWatch for monitoring, S3 for data storage, Lambda for orchestration, and RDS for result storage, supporting the end-to-end ML lifecycle.

Why Walla Chose Avahi

Avahi’s proven expertise in MLOps and AWS-native architectures made it the ideal partner for productionizing Walla’s churn prediction system. Avahi had previously delivered a successful proof-of-concept and was already familiar with Walla’s goals and data. Their deep knowledge of SageMaker pipelines, CI/CD automation, and realtime inference helped accelerate implementation and ensured a robust, maintainable solution.

Solution

Avahi redesigned Walla’s churn prediction platform by implementing a modular, automated MLOps pipeline on AWS:

  • The solution ingests data from structured CSVs (e.g., bookings, subscriptions) via S3 triggers. A Lambda function initiates SageMaker pipelines when new data is uploaded.
  • A preprocessing stage performs schema validation, feature extraction, and transformation.
  • Avahi replaced the decision tree with a tuned XGBoost model, selected for its superior AUC performance and native feature importance capabilities. The model achieved an AUC of 0.846 on validation data.
  • The SageMaker pipeline handles model training, evaluation, conditional registration, and deployment to endpoints.
  • A monthly or performance-triggered retraining workflow ensures model freshness using SageMaker Pipelines.
  • An inference pipeline provides real-time predictions with LIME-based explanations, helping users understand the key drivers behind each churn risk score.
  • Avahi also implemented CI/CD for Lambda functions, managed in a dedicated GitHub repo with Docker-based builds and automatic updates.

Key Deliverables

  • Automated ML pipeline for training, evaluation, registration, and deployment
  • Real-time inference endpoint with LIME explainability
  • Scheduled and performance-based retraining pipeline
  • Deployment scripts, CI/CD integration, and Lambda automation
  • Stakeholder-friendly explainability outputs
  • Monitoring with CloudWatch and model versioning

Project
Impact

The production grade MLOps system delivered by Avahi significantly enhanced Walla s ability to predict and act on gym member churn. Studio owners now benefit from automated insights that identify at risk members and the reasons behind their likelihood to churn, helping drive timely engagement and retention.

Metrics

  • AUC score: 0.846 on validation set
  • Model retrains monthly or on performance degradation
  • Inference pipeline generates individual explanations with LIME
Explore Our Services

We highly recommend Avahi as a reliable and innovative technology partner. Their expertise in cutting-edge technologies was instrumental in building our Proof of Concept (PoC) and developing our Minimum Viable Product (MVP). Avahi consistently delivered high-quality solutions on time while maintaining a collaborative, responsive approach. They went beyond expectations by identifying opportunities for enhancement, ensuring scalability and compliance for our law enforcement-focused products. Avahi is the clear choice if you need a tech partner with industry knowledge, professionalism, and a commitment to innovation.

Brandon Puhlman

Founder, Bravo Foxtrot

Ready to Transform Your Business with AI?

Book Your Free Ignition AI Workshop

Let’s explore your high-impact AI opportunities together in a complimentary half-day session
Book Your Workshop

View Our Case Studies

See how we’ve delivered measurable results for businesses like yours
View Case studies