When I look back at the last few years, I realize this project wasn’t something I created overnight. It grew out of years of working with clients, listening to their frustrations, and seeing the same challenges appear again and again in their quality assurance processes.
I’ve been in QA for over 15 years, testing everything from small mobile apps to complex enterprise systems. Over time, I noticed that many projects - regardless of the industry or company size - were struggling with the same problems: unbalanced workloads, too much manual testing, unclear documentation, and a lack of measurable QA results.
At first, I didn’t think about creating a new product or service. My initial goal was simply to understand these problems better. I started gathering points from client conversations, writing them down, and comparing them across different projects. It quickly became clear that patterns were emerging - the same issues kept repeating.
Building the Foundation
Once I saw the patterns, I decided to make it more structured. I created a detailed survey that would help me collect consistent information from every client. I didn’t outsource it - I designed every question myself, thinking about what would give me the clearest picture of a QA process. I tested it, refined it, and then started using it with new clients.
The first version was simple - I would send the survey, collect the answers, and then manually go through the responses. I analyzed the results, identified the biggest pain points for each project, and created a written analysis for the client. It was a lot of manual work, but it helped me learn exactly where QA processes tend to break down and what changes bring the most improvement.
Pain Points and Real Change
One of the most useful parts of this early work was the Pain Point Analysis. For each major issue, I would break it down into:
- The root cause - why it kept happening
- The risks of leaving it unaddressed
- The actions that could solve it
- The benefits the client could expect if they made the change
This format made it easier for clients to act. And when they followed through, the feedback was very positive - many told me that having such a clear, step-by-step outline helped them make changes faster and with less resistance from their teams.
Inventing the QA Maturity Level
After working manually like this for quite a while, I wanted to find a way to show clients not just a list of problems, but a clear visual of where they stand today and where they could be.
That’s when I created the QA Maturity Level.
It was a scoring model based on key areas like automation coverage, process consistency, tool usage, AI adoption, and stakeholder visibility. Each category had a score, and the total gave an overall maturity percentage. This made it much easier for clients to understand their current state and track improvement over time.
Bringing in AI
Only after building this whole system manually - the survey, the analysis, the maturity model - did I decide to bring in AI. The idea wasn’t to replace my expertise but to speed up the process so clients could get results faster.
Now, instead of spending days manually processing survey responses, the AI helps me quickly identify patterns, compare them against industry benchmarks, and produce a structured report. This allows me to spend more time on the parts that matter most - interpreting the results, discussing them with the client, and helping them implement the changes.
Looking Back
When I think about this journey, I’m proud that it started from something very simple: listening to my clients and writing down what I heard. Over time, it grew into a complete framework that helps companies save time, cut costs, and improve their QA processes in a measurable way.
And even though AI is now part of it, the heart of this audit is still the same as in the beginning - it’s about understanding people’s real problems, finding the root causes, and helping them create a QA process that truly works for them.
Why This Audit Matters
For me, this audit is not just another tool — it represents years of accumulated experience and lessons from real projects. I’ve seen how teams, even highly skilled ones, can get stuck in inefficient patterns: repeating the same manual tasks, struggling with workload swings, or missing important details simply because their process doesn’t support them.
That’s why I believe this audit is so important. It gives both managers and QA teams something they rarely have: a clear, structured way to see where their process stands and what exactly needs to be improved. It turns vague frustrations into measurable problems and then into practical solutions.
The real value lies in what it prevents. Every bug that slips into production costs money, every testing delay pushes delivery back, and every imbalance in workload affects morale. By addressing these problems systematically, the audit helps organizations save time, reduce unnecessary costs, and give their teams the tools to work more effectively.
For me, this is not just about quality assurance — it’s about creating confidence. Confidence that deadlines can be met, that software will perform as expected, and that the team’s effort is being used in the best possible way.