From Reliability Crisis to Scalable AWS Foundation: How Athlete.ai Got to Production-Ready in 45 Days – Platformr
Customer Story

From Reliability Crisis to Scalable AWS Foundation: How Athlete.ai Got to Production-Ready in 45 Days

Athlete.ai Multi-Tenant SaaS AWS Migration
Platformr
Athlete.ai
$25K
Savings on professional services
45 Days
To production-ready AWS environment
0
Compromises on reliability or security
Background

A fast-growing app, a fragile foundation

Athlete.ai is a B2C mobile application that creates personalized highlight reels for coaches, players, parents, and fans. As the platform gained traction, its multi-tenant SaaS architecture needed to scale with it.

The company had recently launched a beta version and was actively collecting user feedback ahead of a production launch. But the infrastructure underneath hadn’t been built to handle growth. The previous development team lacked cloud architecture experience, and the gaps were showing up fast — as reliability issues, performance degradation, and an inability to understand what the platform actually cost to run per tenant.

Athlete.ai needed to move to AWS and do it right. They chose Platformr to get them there.

Athlete recording a highlight reel on a mobile phone at a basketball court
Athlete.ai turns moments like this into personalized highlight reels for coaches, players, parents, and fans.
The Challenge

Scaling reliable infrastructure with better cost visibility

Foundation problems always compound: reliability and performance issues started surfacing as the user base grew, and the underlying infrastructure couldn’t be patched incrementally — it needed to be rebuilt correctly from the start. Their previous provider couldn’t deliver the scale or visibility they needed. The decision to migrate to AWS was straightforward. Executing it without disrupting beta operations, and doing it within a budget that fit a growing startup, was the challenge.

Infrastructure that couldn’t handle growth

Reliability and performance issues surfaced as the user base grew. The previous development team lacked cloud architecture experience, and the gaps couldn’t be patched — the foundation needed to be rebuilt correctly from the start.

No visibility into cost per tenant

With a multi-tenant pricing model that depended on understanding what each customer actually cost to serve, the blind spot made it nearly impossible to set prices with any confidence.

The Solution

Foundation + Workload Factory: a secure, scalable AWS environment built for growth

Platformr deployed a complete AWS foundation for Athlete.ai, combining automated environment setup with the governance, cost visibility, and operational structure the company needed to scale.

Foundation included:

  • AWS Landing Zone and organizational governance
  • Tagging policy for per-tenant cost visibility
  • Backup and security policies aligned to business requirements

Workload Factory included:

  • Separate environments for Development, Testing, Staging, and Production
  • A Disaster Recovery environment to protect against data loss

Platformr was a game changer. It solved our reliability issues immediately, and set us up for success with a scalable solution. Getting visibility into our cloud costs also helped us calibrate our pricing model to maximize revenue and profitability.”

Kevin Keranen, CEO — Athlete.ai
Results

A platform built to scale and a pricing model built to profit

$25K savings on professional services

Automating the provisioning process eliminated significant manual DevOps work, delivering a substantial reduction in implementation costs.

Implementation timeline of 45 days

Athlete.ai completed its migration to a fully structured AWS environment in 45 days, moving from an unstable foundation to production-ready infrastructure without disrupting active beta operations.

Reliability resolved from day one

Auto scaling, backups, and separate development environments addressed the reliability and performance issues that had been limiting the platform’s ability to grow.

Per-tenant cost visibility

With tagging in place across the AWS environment, Athlete.ai could finally see what each tenant cost to serve, giving their team the data needed to build a pricing model grounded in actual usage.

Infrastructure built for what’s next

With separate environments in place, Athlete.ai now has the structure to support A/B testing and parallel development feature branches, and a robust framework ready to meet compliance requirements as the business grows.

Get Started

Ready to build your AWS foundation the right way?

See how Platformr can help your team get to AWS faster, with the security, governance, and cost visibility you need from day one. Get in touch