Work
Every engagement starts with a diagnostic. Here is what that looks like in practice — a full AI Readiness UX Audit, anonymised where required.
AI Readiness UX Audit
South London home care provider
The brief
A mid-sized home care provider in South East London came to Xyra Foundry through a referral. They had a functioning website, a Google-optimised presence, and a strong local reputation.
AI visibility wasn't a priority, however what the audit uncovered changed that quickly.
What we found before we even started the audit
When we ran the initial AI scan, the business wasn't appearing in AI-generated search results for the queries their prospective clients were actually using. Searches like "home care providers in [area]" and "live-in care South East London" were returning competitors, generic directories, and in one case, a business that had since closed.
That alone would have been enough to justify the audit.
But then we found something they hadn't anticipated: an aggregator site was surfacing their pricing in AI responses. Not their current pricing. An old rate. And the business had no idea.
For a home care provider, where families are making emotionally loaded, high-stakes decisions, this matters. A prospective client asking an AI assistant about care options may have already formed a view about what this company charges before they pick up the phone. That expectation doesn't come with a correction.
The audit
We ran a full 30-point AI Readiness UX Audit across four pillars: Discoverability, Entity Clarity, Content Extractability, and Decision Journey Readiness.
Overall score: 52 out of 100
Pillar
Score
Discoverability
Entity Clarity
Content Extractability
Decision Journey Readiness
Overall
67%
67%
42%
42%
52%
The headline numbers tell part of the story. The detail tells the rest.
Discoverability and entity clarity were functioning at a baseline level. The business existed in the AI's frame of reference. But existing is not the same as being recommended.
Content extractability scored 42%. AI systems are built to extract and synthesise structured information. When that structure isn't there, the AI skips what it can't parse and moves on to a source that's easier to read. For this provider, significant content describing their services, their care model, and their team was effectively invisible to AI, because it wasn't structured in a way that AI could lift and use.
Decision journey readiness scored 33%. This is the pillar that most businesses overlook entirely. It assesses what happens after an AI refers someone to your website. Families searching for home care don't land on a website in exploration mode. By the time they arrive, they've typically had multiple AI conversations already. They know what they want. They're looking for confirmation. A website that treats them like a first-time visitor will lose them.
What the diagnostic revealed
This audit wasn't about building a new website or overhauling an SEO strategy. It was about understanding precisely where the gap exists and what it's costing.
The diagnostic identified:
-
The specific queries where the business was absent from AI results
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The aggregator source publishing outdated pricing, and what would be required to address it
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The content gaps preventing AI from extracting and citing service information accurately
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The UX decisions creating friction for visitors who arrived already decision-ready
Each finding came with a clear explanation of why it mattered and a prioritised recommendation for what to address first.
The value of knowing
This provider now knows exactly where AI is bypassing their website. They know exactly how they're being represented in AI results when their name doesn't make the shortlist. And they have a prioritised list of fixes, ordered by impact on the decision journey rather than technical complexity.
That's what an AI Readiness UX Audit delivers: not a theory about AI search, but a precise diagnostic for your specific business, on your specific website, against the queries your actual clients are using.