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How Synli scans: our methodology

Synli builds on the open-source axe-core engine run through Playwright, then layers AI vision and Nordic-localized findings on top — and is honest about what automation can and cannot verify.

Accessibility tools are only useful if you can trust what they claim. This page explains exactly how Synli scans, which parts are automated, where human review is still required, and the regulatory details we encode so a report reflects the rules that actually apply to you.

Built on axe-core, extended by Synli

Synli's automated rule pass is powered by axe-core, the open-source accessibility engine (MPL-2.0) that also powers the axe DevTools used widely across the industry. We run it through Playwright so pages are evaluated in a real browser, including states a static parser would miss. Naming the engine matters: detection is a shared commodity layer, and we would rather be transparent than imply a proprietary black box.

On top of the engine, Synli adds AI-assisted vision analysis that proposes whether an image's alt text describes the image, Nordic-localized rule output, authenticated scanning, confidence metadata, and structured statement drafts. The official Norwegian statement still requires human confirmation and publication on uustatus.no.

The scanning pipeline
  1. CrawlPlaywright visits reachable pages and authenticated states within the configured scope
  2. Rule passaxe-core runs the deterministic WCAG checks
  3. AI layerVision and semantic review candidates for judgement-heavy issues like alt-text quality
  4. Map & scoreFindings linked to WCAG criteria with a confidence level
  5. ReportTool-verified vs needs-review, with a uustatus.no copy helper and Markdown export

What automation can and cannot verify

Automated rules can evaluate only a subset of WCAG questions; the exact share varies by solution, content and test coverage. Synli separates tool-verified results from items needing human review and does not treat an automated scan as a conformance decision.

  • Reliably automated: colour contrast ratios, missing alternative text attributes, form labels, language attributes, name/role/value exposure, and many ARIA misuse patterns.
  • Requires human judgement: whether alt text is meaningful, logical reading and focus order, link text in context, error-recovery quality, and whether content makes sense to assistive technology users.
  • Synli's AI layer narrows the gap on some judgement calls (notably alt-text quality) but is presented as assistance for a human reviewer, not a replacement.

Norwegian 48/42 and 35/29 profiles

Norwegian technical baselines vary by sector and solution type. Uutilsynet lists 48 requirements for public-sector websites and 42 for public-sector apps. Covered private websites use 35 Level A and AA criteria from WCAG 2.0, while covered apps use 29 WCAG 2.1 criteria. Synli builds a profile from your organisation and solution inputs, but legal scope, exemptions and unusual cases remain a scope check for the organisation.

Synli does not replace manual accessibility review. It makes issues clearer, separates verified findings from items needing a human check, and structures the output so the remaining human work is targeted and fast.

Sources