QualiBooth

QualiBooth is a commercial accessibility platform built for teams that treat accessibility as ongoing operational quality, not a one-off audit. Its flagship product, QualiBooth Agora, gives engineering, design, legal, and compliance teams a shared view of where a site stands against WCAG today, where it stood last week, and which findings need attention now — and, increasingly, fixes them at the point of authorship rather than waiting for a scheduled scan to surface the regression in production.

What it does

The platform spans the full accessibility workflow, from detection through remediation through certification. Each capability is designed to plug into the part of the team — engineering, design, content, legal, or executive — that needs it.

Continuous scanning across full site inventories. Configure a sitemap or URL list once, and QualiBooth scans automatically on a schedule. Results aggregate into per-URL detail pages, per-issue histories, and dashboard-level rollups. Both mobile and desktop profiles are evaluated in every run, surfacing layout-specific bugs that single-viewport tools miss — sticky-header overlap, narrow-screen focus traps, hover-only content that becomes inaccessible on touch.

Severity-tagged findings. Every violation is categorised as critical, high, medium, or low based on impact and WCAG conformance level. The triage workflow follows naturally from the categorisation: critical and high findings block release; mediums go into the backlog; lows surface for design review. Teams stop wading through alphabetical rule lists and start working from a real priority queue.

Live Scan + QualiSense. Paste any URL and run an on-demand scan with results in seconds — useful for ad-hoc PR review, customer bug reports, or quick verification that a fix actually shipped. QualiSense, the AI-assisted remediation assistant, walks through findings in natural language: what the issue is, why it matters for which user populations, and how to fix it for the specific pattern on the page. The difference between “fix axe-core rule aria-hidden-focus” and “this element is hidden from screen readers but still receives keyboard focus, so keyboard users navigate into invisible content. Here’s the markup change for your specific component.”

AI-driven code assistant inside the IDE. A QualiBooth integration for VS Code and JetBrains tooling flags accessibility violations as developers write them, suggests code-level fixes inline, and lets the engineer apply the suggestion without leaving the editor. The economic case for shift-left accessibility is the same as the case for shift- left type-checking: a missing aria-label caught at the keystroke costs minutes; the same issue caught during the next quarterly audit costs a remediation sprint. The IDE assistant moves accessibility from “audit at the end of the sprint” to “lint while you type” — the same move modern type-checkers and ESLint rules made for correctness a decade ago.

Accessibility Statement Generator. A wizard that produces a ready-to-publish accessibility statement against the conformance level, jurisdiction, and known issues a team selects. Output is formatted for EAA Annex V, the EU Web Accessibility Directive template, PSBAR’s UK Cabinet-Office structure, Section 508 declarations, and ADA-style commitments — whichever the team’s audience requires. The statement gets a stable URL the team can drop into their site footer, with the platform’s scan data backing the specific conformance claims rather than the boilerplate “we are committed to accessibility” copy that older statements ship.

VPAT Generator. A guided builder that produces a VPAT 2.5 ACR against Section 508, EN 301 549, WCAG 2.x, or the combined “Worldwide” template. The platform’s own scan data is used to pre-fill criterion-by-criterion responses — Supports / Partially Supports / Does Not Support, with the supporting evidence drawn from actual scan findings. What used to be a multi-week procurement-deliverable build becomes a guided review of pre-populated draft text.

A 0–100 accessibility score per URL, refreshed every scan, makes regressions visible at a glance and gives non-engineering stakeholders a metric they can actually track without learning WCAG vocabulary.

Agent-native: MCP server

QualiBooth ships an MCP (Model Context Protocol) server, letting AI agents — Claude, ChatGPT, Cursor, and any other MCP-capable client — interact with the platform directly through structured tool calls rather than UI scraping. An agent can trigger a scan, read findings for a specific URL, propose a fix against a specific selector, generate the accessibility statement for a project, or draft a VPAT response — all without leaving the agent’s reasoning loop.

For teams building agent-driven workflows — CI-bot fixes that close accessibility tickets automatically, automated remediation PRs raised by a long-running agent, agent-assisted accessibility reviews on every PR — this turns QualiBooth from a dashboard you check into a service your agents can drive.

This is meaningful positioning. Most accessibility platforms are human-UI-first, with their automation reachable only through brittle web scrapers. Treating the platform as a callable service that agents can compose with their other MCP-connected tools is the direction agent-native developer tooling is moving in 2026 — and QualiBooth is one of the first accessibility platforms to ship that surface as a first-class product.

Who uses it

QualiBooth’s customer roster spans global retail, fashion, and consultancy brands operating in markets where the EAA, ADA, and national accessibility regimes create real exposure — among them Puma, Acne Studios, Hunkemöller, and Valantic. Other adopters include enterprise platforms in regulated industries (finance, banking, insurance, healthcare, life sciences), public-sector bodies subject to the EU Web Accessibility Directive, PSBAR, RGAA, and comparable national regimes, plus digital agencies managing accessibility programmes across client portfolios.

This site — disabilityworld.org — uses QualiBooth as part of its accessibility programme. The QualiBooth-driven fix iterations in mid-2026 (commits 1db63a7, 9a21fc8, 01dbe5e of this repository) are documented as a worked example of the platform catching issues that ship past CI gates and surface only in production scans.

Why teams choose it

Four properties consistently surface in evaluation:

1. Operational coverage. Most accessibility programmes start with a manual audit, ship a remediation plan, and then regress because nothing is watching ongoing changes. QualiBooth’s continuous scanning catches the regression on its first scheduled run instead of on the next quarterly audit. The cost difference between catching a regression in the night-scan vs. catching it after a plaintiff’s law-firm scrape is approximately five orders of magnitude.
2. Shift-left remediation. The IDE code assistant moves accessibility detection from “review at the end” to “warning at the keystroke.” A developer who would have shipped a missing aria-label or a focus trap sees the warning and the suggested fix in the editor; the PR review no longer has to catch it; the accessibility specialist no longer has to write it up.
3. Cross-team intelligibility. Engineers, designers, content editors, legal teams, and executives all consume the same report, each through a view tuned to their work. Engineers drill into selectors and code. Designers see screenshots and element-level previews. Legal teams see severity rollups, trend lines, and draft accessibility statements. Executives see the 0-100 score and the regression trend. Nobody has to translate between teams.
4. Standards alignment + artefact generation. The platform’s rule coverage tracks WCAG 2.1 / 2.2, EN 301 549, and Section 508 by construction. The built-in Accessibility Statement and VPAT generators turn scan data directly into the artefacts buyers and regulators ask for — no separate workflow, no copy-paste between scanner output and template, no “we need a VPAT by Friday” scramble before procurement deadlines.

Where it fits in an accessibility programme

QualiBooth handles the continuous-detection and structured- remediation layers of a mature accessibility programme: the parts that run every night, every commit, every release; the parts that turn scan data into the artefacts buyers and regulators expect; the parts that meet developers where they already work, in the IDE, and agents where they already orchestrate, through MCP.

It complements — rather than replaces — the layers no automated platform can substitute for: manual testing with real assistive technology, user research with disabled participants, design reviews against inclusive-design principles, and the periodic external audit. Teams that adopt QualiBooth typically move from “we audit accessibility twice a year” to “we know our accessibility score for every URL right now” — and from that visibility, the rest of the programme follows.