2.7 Million Tests, Zero Bottlenecks: How Best Egg Built Financial Trust Through Robust QA

About Best Egg

Best Egg is the leading consumer financial technology platform. It provides flexible solutions to help people with limited savings confidently navigate their everyday financial lives.

They support customers through a growing suite of personal loans, financial health tools and even vehicle equity loans. Their services help customers overcome medical debt, plan weddings, fund vacations, and complete home improvements.

Best Egg prioritizes strong client relationships, delivering tailored financial support within a seamless digital experience. Their commitment to accuracy and customer satisfaction establishes their reputation as a trusted partner during stressful financial decisions.

The company's name reflects their mission: becoming customers' best financial nest egg during significant life transitions.

As Tenny emphasizes, The stability and reliability of our core product is the foundation of our brand promise. Our customers need absolute confidence in our platform. And we aim to deliver that".

When Good Solutions No Longer Support Growth

Best Egg's in-house testing infrastructure supported their journey from a startup to an established fintech company.

But it could no longer support their expanding customer base and product line.

Their existing testing approach faced multiple critical challenges:

• Time-consuming execution: Tests took more than an hour to complete, creating release bottlenecks. "Why has it been an hour and it still hasn't outputted our results?" was a common frustration.
• Poor reporting infrastructure: Their system used "a very basic bootstrap application" that often displayed test steps out of order. "The screenshots weren't timed well and didn't add much value when reading test results."
• Technical barriers: The Java-based testing solution was "too heavy" with "way too much boilerplate code," making it difficult for testers to focus on test logic and instead spend more time writing test code.
• Limited test coverage: "Most of our tests were not emulating different browsers. We'd get the latest version of Chromium and run it on that," resulting in minimal coverage for other browsers like Firefox, Edge, older browser versions, and mobile devices.
• Dependency on engineers: When tests failed, the team needed to go to an engineer and ask, 'Why did this fail? What do these results mean?' This created bottlenecks for testers and diverted engineering resources.

Best Egg also used a cloud testing platform for simulating different devices and browsers. However, the platform was built across monolithic architecture, making it difficult to integrate properly with their regression infrastructure and thus, couldn't be used effectively.

These limitations affected their ability to meet quality demands and release software efficiently: The platform ended up bottlenecking our releases. We had to ask for developer's valuable time to help us with fixing QA issues, time that could've been spent working on something more important.

How TestMu AI Helped Best Egg Make Testing Easier for Everyone

Best Egg came across TestMu AI that checked all their requirements and helped modernize their testing approach.

Parallel Testing - Easy to scale test infra - Time

With TestMu AI reliable and scalable infrastructure, Best Egg was able to achieve parallel test execution for both mobile and web.

We're executing our mobile tests at the same time as our web tests, which was not a world that we lived in in the past.

This parallel execution capability supports Best Egg's impressive testing volume:

• 2.7 million automation tests completed (both web and mobile)
• 128k native app tests executed over real devices

AI-Native Intelligence Eliminates Manual Testing Overhead

Best Egg's testing bottlenecks went beyond just infrastructure constraints. They were trapped in manual processes that required constant human intervention and engineering support.

HyperExecute's AI-native test orchestration platform transformed Best Egg's testing from a manual, error-prone process into an intelligent, self-managing system.

The platform's AI capabilities automatically handle the complex decisions that previously required engineering time: intelligently splitting test workloads for optimal performance, reordering tests based on failure patterns and dependencies, and automatically retrying failed tests to distinguish real issues from transient glitches.

This intelligent automation addressed Best Egg's core challenge of engineering dependency. Instead of developers spending time troubleshooting test infrastructure and analyzing false positives, the AI handles these routine decisions automatically, allowing the team to focus on actual product development.

The result was a complete shift from reactive testing support to proactive, autonomous test execution. This shift helped Best Egg scale their testing volume to 2.7 million tests without proportionally scaling their engineering overhead.

Real Devices Cloud for Multi-Platform Testing

Real device testing became central to Best Egg's strategy. We could test the native app to see if it works on a Samsung Galaxy or any other device on demand," Tenny notes. Real device testing gave us more confidence compared to simulated tests".

This comprehensive approach made sure Best Egg could reliably test across the diverse devices their customers use: from modern smartphones to unexpected platforms.

We've even seen weird stuff where people run these apps on their Xbox or on their smart fridge," Tenny mentions.

And being able to test across varying screen sizes has helped ensure all these out-of-the-box use cases are handled well.

AI-Native Test Intelligence for Smarter Insights

TestMu AI provided AI-native comprehensive test insights that everyone could understand, not just limited to the technical staff.

This created an intuitive dashboard that anybody can look at and feel empowered to identify the problem, true failure vs. a false positive, etc.

The team could now look at flaky test trends, classification of errors, and notification updates.

TestMu AI's Language Flexibility Helped Rid Development Constraints

Best Egg's previous testing infrastructure locked them into a single programming language approach that created unnecessary barriers for their team. Their Java-based solution required excessive boilerplate code that distracted from actual test logic, regardless of their team's preferences or expertise.

"The Java solution was too heavy for our needs," notes Tenny. There's way too much boilerplate code required, which becomes a barrier to efficient testing.

TestMu AI's support for all programming languages and frameworks gave Best Egg the freedom to choose the right tool for their team and business needs. This flexibility allowed them to optimize for speed and accessibility rather than being constrained by platform limitations.

By removing language barriers, Best Egg could select Python for its simplicity and broader team familiarity, dramatically reducing development time and expanding who could contribute to testing efforts.

"More people know Python," Tenny adds. It makes it a lot easier and faster to write tests that way. For the demands of our business, we need people to be able to write tests fast.

This language flexibility became a key enabler for Best Egg's testing scalability and team efficiency.

TestMu AI automation testing platform supports all programming languages and frameworks, helping us get rid of our excessive dependency on Java. We were able to transit to Python, which helped reduce our lines of code.

Results That Spoke Volumes

TestMu AI helped change Best Egg's testing workflows with measurable, dramatic improvements across every part of their quality assurance efforts.

• 75% Faster Test Execution: Test execution times dropped from a full hour to approximately fifteen minutes. It just feels more on demand," Tenny explains.
• 2.7 Million Automation Tests: Best Egg now powers through 2.7 million automation tests and 128,932 real device tests, volumes previously unthinkable. This ensures flawless performance across diverse customer devices.
• Zero Engineering Bottlenecks: "There's less context switching for engineers. Engineers write more tests or more features," notes Tenny. Technical talent now drives innovation rather than troubleshooting infrastructure.
• 100% Release Confidence: "We're able to release faster because we can test more. We have better test coverage. It increases confidence in the platform," Tenny shares, confidence that extends to customers making critical financial decisions.

What's Next for Best Egg

Best Egg continues iterating and improving their approach.

While Best Egg is currently focused on building out infrastructure for their current testing platform, they plan on experimenting with Kane AI for test authoring.

"TestMu AI helps us meet the demands of the changing environment as a fintech company, giving us the assurance and confidence to deliver best-in-class experiences," summarized Tenny.

For Best Egg, quality is central to their brand promise of supporting customers at life's most important financial moments.