Case Studies

How we've helped teams release faster, launch AI safely and stay online when it matters most.

Vibe-coded consumer website

QA for a vibe-coded website before launch

The challenge: A 22-page consumer website had been built almost entirely with AI coding tools. It looked finished, but it had never been tested systematically, and nobody could say with confidence what problems the AI-generated code was hiding.
What we did: We put the site through our full QA process: cross-browser and device testing, performance, security and accessibility testing, and testing of both the frontend and the backend. Every bug was logged with steps to reproduce, prioritized with the team, and retested once fixed.
Results: 73 bugs found across the 22 pages, all fixed and retested before launch
Private API keys exposed in a public code repository, caught before launch
Cross-site scripting (XSS) and SQL injection holes in the contact form closed by sanitizing submissions
Data that was being posted in plain text, caught and fixed

Telehealth

Bringing a telehealth portal with AI chat to life

The challenge: A new telehealth portal needed to be tested end to end before launch, including its AI chat features. In a healthcare product, the AI chat had to stay on the subject of telehealth and not drift into topics it shouldn't discuss.
What we did: We combined AI-assisted, automated and manual testing: cross-browser and device testing, performance, security and accessibility testing. We tested the AI chat features in depth and helped train the AI to stay within defined guardrails, so it sticks to the subject at hand.
Results: Telehealth portal brought to life with automated and manual test coverage
AI chat held to defined guardrails, staying on the subject of telehealth
Tested across browsers and devices for performance, security and accessibility

Healthcare SaaS

Evaluating a patient-support AI assistant

The challenge: A patient-facing AI assistant was ready to launch, but the team had no way to measure whether its answers were accurate or safe.
What we did: We built a 400-prompt evaluation set with a clinical-safety rubric, red-teamed the assistant for prompt injection and data leakage, and set up an automated eval pipeline that runs on every prompt or model change.
Results: Out-of-scope medical advice reduced from 9% of test responses to under 1%
Two data-exposure paths found and fixed before launch
Eval suite now gates every AI release

E-commerce

Load testing an online store before peak season

The challenge: Traffic during the previous year's holiday sale had taken the store offline for most of an afternoon.
What we did: We modeled peak-season traffic with k6, ramped to five times normal load, and worked with their developers to trace and fix each bottleneck, starting with database connection pool exhaustion at 2.5 times normal traffic.
Results: Store handled 5x normal traffic in testing
Zero downtime through the following peak season
Checkout page response times improved by 40%

What clients say

"TopNotch is our go to team for all things digital. AI, QA, Development. You name it, they will do it right."
Maria Viejo, VP Engineering

"Process had always been a pain point in our SDLC. Not only did TopNotch help eliminate those troubles, they also improved our overall deliverables beyond measure."
Jason Schertz, CTO

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