Labrador is a guided accessibility testing platform that centralizes manual WCAG 2.1/2.2 audits in a single web app. It provides in‑app criterion summaries, AI‑assisted remediation suggestions, and page/component‑level tracking, with searchable, sortable project organization and exportable reports for accessibility consultants.
Funding
Funding not disclosed
Founders
Product
Problem
Manual WCAG 2.1 and 2.2 compliance audits often rely on spreadsheets and disconnected notes, making it difficult for accessibility consultants to keep test results organized, searchable, and actionable across multiple pages and components.
Solution
Labrador offers a guided accessibility testing platform that centralizes manual WCAG audits within a single web application. The tool presents in‑app criterion summaries and testing tips for each WCAG rule, allowing consultants to conduct page‑ and component‑level assessments without leaving the interface. AI‑assisted remediation generates contextual suggestions directly from the inspected HTML, which can be edited and exported to developers. Projects are organized with searchable names, sortable dates, and grid or list views, enabling quick navigation and progress tracking across large sites. The platform streamlines the workflow from discovery through delivery, reducing reliance on external spreadsheets and improving audit consistency.
Target Audience
Primary users are accessibility consultants and agencies that perform manual WCAG compliance audits for client websites and applications.
Features
- Guided testing flow with built‑in WCAG 2.1/2.2 criterion summaries and tips
- Page and component level audit tracking with progress indicators per item
- AI‑driven remediation suggestions generated from selected HTML snippets
- Centralized project dashboard with searchable, sortable, and view‑mode options
- Exportable reports that can be shared directly with development teams