Content QA at Scale | AI-Native QA for Content Platforms

The problem

Manual review does not scale with a content calendar.

A course goes live with a broken video embed. A listing publishes with a thumbnail that never loaded. A human reviewer catching those before launch is a linear cost against a catalog that keeps growing, and review quality depends on who did it and how much time they had that day. Content QA ends up as a launch gate: the thing standing between "ready" and "published," and it gets slower exactly when the content calendar gets busier.

How it works

Every item, checked the same way, every time.

Point Donobu at what "checked" means for one item.

Describe what a course, listing, or article needs to pass, in plain language, the same way you'd describe a user journey for functional testing.

Agents traverse the real rendered experience.

Not a database record or a CMS field: the actual page a learner or shopper would land on, seen the way they'd actually see it.

Every item gets checked against the same list.

Rendering, broken media and links, layout, and whether the text reads right in context, plus locale variants where a content unit ships in more than one language.

Our engineers review before you do, and you pay per item.

AI agents do the traversal and the first pass. Forward-deployed engineers in test (FDETs) author what "checked" means for your content, and SDETs review results before delivery. Pricing is usage-based: per item checked, not a flat contract sized for your busiest month.

Proof

Coursera uses Donobu to QA content before launch, paying for outcomes rather than tester-hours.

Ownership

Findings you keep, not a report you file away.

Every content check runs the same way every other Donobu test does: local-first, on your machine or in your VPC. A rendering issue on your top course can become a real Playwright test in your own repo, one you can re-run on the next launch instead of re-checking by hand. See the full case for owning your tests.

More ways teams use Donobu

Functional testing

Turn critical user journeys into a regression suite that never goes stale.

See functional testing

Exploratory testing

Point an agent at your app and see what's actually broken, no script required.

See exploratory testing

Mobile app testing

Test native Android and iOS builds the same way you test the web.

See mobile app testing

Localization QA

Continuous QA across every market and locale you ship.

See localization QA

FAQ

Frequently Asked Questions

What counts as a "content item"?

A course, a listing, a catalog entry, an article, or a similar published unit, checked as the whole rendered experience rather than as isolated fields in a CMS.

How is content QA different from localization QA?

Localization QA checks whether your product works correctly in a given locale: layout, translated strings, locale-specific logic. Content QA checks whether a content unit is ready to publish: rendering, broken media and links, layout, and text quality in context. The two overlap where a content unit ships in multiple languages, which is where content QA's locale-variant checks come in.

Is this fully automated?

No. AI agents do the traversal and the first pass. Our engineers author what "checked" means for your content and review results before they reach you: the same FDET-authors, SDET-reviews model Donobu uses across every managed offering.

What does it cost?

Usage-based, per item checked. Cost scales with your content calendar instead of a flat contract sized for your busiest launch month.

Get started

Ready to see what Donobu finds in your content before launch?

Book a demo

QA for content at scale, before launch.