Ensuring digital accessibility is crucial for inclusivity, legal compliance (meeting standards like WCAG 2.1/2.2 AA, ADA, Section 508, AODA), and enhancing overall user experience, which positively impacts SEO and brand reputation. However, achieving and maintaining accessibility can feel like navigating a complex, ever-shifting landscape. Manual audits are essential but resource-intensive and often performed too late in the development cycle.
The Cassiopeia AccessAssist Engine, developed internally at Litza Tech, integrates directly into the web development lifecycle or acts as a persistent monitoring guardian for live sites. Unlike simple browser extensions or surface-level scanners, Cassiopeia performs a deeper dive. It meticulously analyzes the Document Object Model (DOM) structure, evaluates CSS for potential issues like insufficient color contrast or reliance on color alone to convey information, and can even interact with JavaScript elements to assess the accessibility of dynamic content and single-page applications. It specifically checks for common but critical failures: missing or inadequate alternative text for images (distinguishing between decorative and informative images using heuristic analysis), improper use of ARIA roles and attributes that can confuse screen readers, forms lacking clear labels or error handling, insufficient keyboard navigability (ensuring all interactive elements are reachable and operable without a mouse, avoiding keyboard traps), illogical heading structures, and ambiguous link text (“click here”).
What sets Cassiopeia apart is its combination of rule-based checks derived directly from WCAG success criteria and a machine learning component. This ML model is trained on a vast dataset of accessible and inaccessible web components, allowing it to identify nuanced patterns and anti-patterns that rigid rulesets might miss, particularly in complex custom widgets or unconventional layouts. When Cassiopeia flags an issue, it doesn’t just report an error code. It provides a clear, human-readable explanation of the barrier encountered, cites the specific WCAG guideline and success criterion violated, and crucially, offers concrete remediation advice. This might include suggested code snippets (e.g., the correct ARIA attribute to add), content recommendations (e.g., how to rewrite ambiguous link text), or design adjustments (e.g., suggesting specific color combinations that meet contrast requirements). For simpler, repetitive issues like adding alt=”” to purely decorative images identified with high confidence, it can queue suggested automated fixes for developer review and one-click implementation. Integration with popular CI/CD pipelines and issue tracking systems (like Jira or GitHub Issues) ensures accessibility checks become a seamless part of the development workflow, fostering a “shift-left” approach where accessibility is built-in, not bolted-on. This reduces costly rework, minimizes legal exposure, expands market reach, and builds websites that truly work better for everyone.
