How We Built AccessCheck

The problem

Most accessibility tools are built for developers, agencies, or compliance teams. That makes sense technically, but it creates a gap for business owners. A local clinic, Shopify store, or services business does not just want a list of violations. They want to know whether the site is risky, what is broken first, and what they can actually do about it.

What we decided to build

We built AccessCheck as a focused web product with one fast entry point: homepage scan, plain-English report, and a clear upgrade path into monthly monitoring. The goal was not to be a giant enterprise accessibility platform. The goal was to make the first useful answer obvious in under a minute.

Where AI actually mattered

The deterministic scanner still matters. That is how we keep findings grounded. But the product gets much more usable when AI translates those findings into practical language, platform-aware guidance, and next actions a business owner can understand.

Later, that same logic extended into the outreach system: using scan data to support internal cold-email workflows, draft generation, and lead qualification inside the admin console.

What had to be engineered around

• abuse resistance on public scan forms
• background worker reliability for running scans and translations
• database migrations and safe production deploys
• billing provider changes when the business shifted from Stripe assumptions to Paddle
• keeping old scan records compatible as reporting evolved

Building the product was not just about the scan engine. It was also about making the system production-safe: deploys, migrations, health checks, smoke tests, billing, and internal admin tools all had to work together.

The growth layer

One of the more interesting things about AccessCheck is that it became more than a customer-facing product. We also turned it into an internal growth engine. The admin system now supports lead import, scanning, draft generation, CSV export, and Hunter enrichment so the same product intelligence can support outbound workflows.

The outcome

AccessCheck is now a live SaaS product with public scanning, PDF export, monthly monitoring, an admin outreach workbench, and a production release process that is strong enough to keep shipping on. That matters because most “AI product” case studies stop at the demo. This one had to operate like a business.

What small businesses can learn from it

The biggest lesson is that the useful AI product is usually the one that makes a narrow workflow clearer, faster, and more actionable. You do not need to start with a giant platform. You need one painful business problem, one fast input, and one strong answer.