Why I Created a11y-engine

Frontend accessibility usually requires multiple tools working at the same time. axe helps with automated scans. Playwright makes it possible to validate real navigation flows. Lighthouse works as a quick audit. Screen readers, keyboard navigation, and manual validation remain an important part of the process. Each tool solves a different part of the problem, but the complete workflow often ends up feeling fragmented and repetitive during development.

The motivation behind a11y-engine came from trying to improve that exact flow. The idea was not to replace existing tools, but to integrate them into a more consistent experience for modern frontend and bring AI directly into the accessibility process. Over time, it became clear that the challenge was not only detecting issues. The real work came after that: interpreting findings, organizing remediation, and keeping processes consistent in day-to-day development.

One of the main goals was to bring different tools into a more connected workflow. axe, Playwright, and structured testing already solved important parts of the process, but they usually lived separately across scripts, reports, audits, and manual reviews. a11y-engine started as a way to bring all of that closer together inside a more centralized flow aligned with how frontend teams actually work today.

AI eventually became an important part of that approach. Not only as an analysis layer, but as a way to help interpret findings, generate technical context, and accelerate remediation processes. Very often, the problem is not finding accessibility errors. The problem is transforming audits and technical results into useful actions for developers working on real components and complex applications.

Another important part of the project was moving accessibility toward the tools teams already use every day. A large part of modern development happens inside GitHub, pull requests, and automated pipelines, so keeping accessibility separate from the main engineering flow never made much sense. Integrating findings and validations directly into PRs and reviews helped accessibility stop feeling like an external task and start becoming a natural part of development.

The same happened with Slack and Jira. Many accessibility problems do not happen because tools are missing, but because the workflow ends up fragmented across reports, tickets, conversations, and manual validations that live in different places. An important part of a11y-engine was trying to connect all of that into a more consistent flow, where automated findings, manual validations, and remediation processes could exist close to where the team already works.

In the end, a11y-engine was created as an attempt to modernize the accessibility workflow for real frontend work. Integrating existing tools, bringing AI into the process, and helping structure testing, validation, and remediation inside an experience that is more useful for modern development.