Customer-facing AI is moving beyond answering questions. It now recommends, decides, books, guides and acts — often connecting a digital conversation to a real-world outcome.
Ironwood independently tests whether AI can reliably serve people with disabilities from request to outcome.
We evaluate whether AI understands accessibility requirements, preserves them through complex tasks, uses reliable information about the real world, avoids unsupported assumptions, and knows when human intervention is required.
Consider a traveller telling an AI agent:
"I use a power wheelchair, cannot walk independently and need assistance at both airports. Help me book my trip."
The interface may be perfectly accessible.
The AI can still fail.
Ironwood tests that gap.
Understanding is not enough. The outcome has to work.
Passing this test requires much more than recognizing the words power wheelchair.
The agent may need to preserve mobility requirements throughout the booking, use authoritative airline and airport information, identify information that cannot safely be assumed, request additional details when necessary, escalate unanswered questions, and ultimately produce an itinerary that works for the traveller.
Ironwood records and scores every material decision along the journey.
An accessibility failure can happen at several different layers.
Ironwood identifies not only that the system failed, but why.
Every Ironwood engagement produces reproducible scenarios, scored outcomes and evidence behind material failures. Testing combines structured evaluation with input from people with lived disability experience and domain specialists.
A focused conversation about your customer-facing AI, the journeys it supports and where accessibility exposure may exist.
If independent testing is not warranted, we'll tell you.
We test your AI against a tailored suite of realistic disability-informed scenarios.
You receive scored outcomes, reproducible evidence of material failures, root-cause classification and prioritized remediation guidance.
AI systems do not stand still. Models change. Prompts change. Tools change. Data changes. Policies change.
Ironwood re-tests critical journeys after changes and tracks whether previously successful accessibility outcomes continue to hold.
Ironwood begins with human-led testing for a deliberate reason:
You cannot automate a methodology you have not yet proven.
Every assessment helps strengthen the scenario library, scoring framework, evidence requirements and understanding of how AI fails people with disabilities.
As those systems mature, repeatable elements of testing can increasingly be automated.
The long-term direction is a continuous assurance layer that allows organizations to test their AI systems repeatedly as models, prompts, tools and underlying data change.
The risk becomes particularly important when an AI interaction determines whether someone can successfully complete a real-world task.
Ironwood is built on more than a decade of operating experience in adaptive commerce through Inclusia Brands — serving people with disabilities, families, clinicians and organizations across North America.
That experience exposed us to something technology teams do not always see:
Accessibility is not an abstract compliance requirement. It determines whether someone can actually participate in the real world.
AI is now becoming part of that journey. Ironwood exists to independently test whether it works.
AI systems increasingly plan, recommend, use tools and complete multi-step tasks. The more responsibility they assume, the more consequential their mistakes become.
If your organization is deploying customer-facing AI, we can help determine where accessibility risk exists and whether independent testing is warranted. The first conversation is free and specific.
Book a 30-Minute Briefing