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QA WolfusedbyBrilliant

How Brilliant uses QA Wolf

ConfirmedVendor case study · Checked Nov 10, 2026
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The use case: how Brilliant deploys QA Wolf

Brilliant uses QA Wolf to automate testing of its interactive, game-like learning app across web and Android, replacing slow manual checks after releases. QA Wolf gives developers and lesson designers fast test results so they can ship without fear of breaking anything.

More reported results

Figures published in QA Wolf’s case study. They are not independently measured by usedby.

8–10 bugs per month

Detecting 8–10 bugs per month saving millions of dollars in top-line revenue.

4–5

Provided the equivalent testing capacity of 4–5 additional QA engineers.

In the customer’s words

In order to be able to achieve the same coverage that QA Wolf provides, and to account for the necessary redundancy when people get sick or go on vacation, would probably require a minimum of four or five full-time engineers.
Jared Silver, Senior Director of Engineering, Brilliant — Source

Other AI tools used by Brilliant

Other public relationships recorded on usedby.

ElevenLabsConfirmed
Explore Brilliant’s AI stack

QA Wolf users in EdTech & E-learning

Companies in the same sector, with public evidence.

PadletConfirmed
See all QA Wolf customers

More stories

Go straight to the source

Based on QA Wolf’s published case study. We check the public evidence; the results are reported by the vendor.

qawolf.com
Last checked
Nov 10, 2026
qawolf.comCaptured QA Wolf case study about BrilliantOpen source capture
What the story claims, and what we checked

What we compared with the page.

  • The figure: 5 minutesChecked

    Printed word for word on the page, near the name of Brilliant.

  • The passage quoted aboveChecked

    Copied word for word from the page, near the name of Brilliant.

  • Brilliant uses QA WolfChecked

    Confirmed line.

  • The result itselfNot checked

    We quote it; we did not measure it.

Manually testing the application after a release was taking hours, even a full day. During that time, developers and lesson planners were split-focused monitoring the latest deploy while trying to focus on the next piece of work.
From the page. qawolf.com