Pratik Patel

Pratik Patel

Founder @ Testdino
59 points

About

As the Founder of Testdino, I’m focused on fixing one of QA’s biggest challenges: lost productivity from flaky test failures and unclear debugging. With Testdino, my vision is to bring true test observability so teams can see why tests fail, how to improve them, and how to boost automation productivity. This gives engineering teams the clarity and confidence to ship faster without compromising quality while saving valuable hours. Before starting Testdino, I spent over a decade leading QA automation and quality engineering for startups and enterprises. I authored the book Make the Move to Automation with Appium, and have helped companies strengthen QA, improve release readiness, and scale to billion-dollar valuations.

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Forums

Aleksandar Blazhev

4mo ago

Does build in public really work?

Every day, I notice fewer people sharing their projects here.

A couple of months ago, build in public felt unstoppable: everyone was posting updates, numbers, roadmaps. Now? The hype seems to be fading or maybe makers are just shipping quietly.

Rohan Chaubey

5mo ago

Product Hunt discontinued coming soon / teaser pages. Did they work for you?

I noticed that Product Hunt discontinued the teaser / coming soon section this week, and I m curious if it did help you build genuine traction? 

My take (from hunting PH launches):

Pratik Patel

5mo ago

From QA Agency → QA SaaS

Most Playwright failures aren t real bugs - You rerun, you scroll CI logs and eventually retry passes.
That's how another hour gone and productivity wasted. In this process Reviews will stall because no one knows if failure is legit or it's flaky tests.

After years running a QA agency, I kept seeing the same pattern across teams. Red builds full of flaky noise. Custom fixes did not scale. So we turned our playbook into SaaS.

We built @Testdino to solve this problem. It reads your execution reports and highlights what matters most right now.

It consolidates different test runs into a single place, creates role-specific dashboards, and prepares historical trends and key metrics to reduce debugging time and reveal meaningful patterns.
Our machine learning models and customized LLMs, trained on thousands of test runs, tag each test failure as Bug, Flaky, or UI Change with a confidence score.
Everything, including runs, PRs, branches, and environments, is kept in one clear view.

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