Overview:
On 05/16/26 probuildsolutionsinc.com scored 69% — **Decent** – Overall, the site looks pretty solid for AI visibility, with a few clear gaps around content credibility signals and offsite consistency that keep it from feeling fully “locked in.”
Executive summary
Score Breakdown (High Level)
- Discoverability: 100% - Overall, the site looks solid for search engines to find, but we didn't see an image or video sitemap included.
- Structured Data: 58% - The homepage schema is technically solid and covers the business details well, though the absence of blog-level markup and author data is a notable gap.
- AI Readiness: 67% - The technical foundation is in great shape with active sitemaps and open access for AI, though we couldn't find a Wikidata entity for the brand.
- Performance: 67% - The homepage mobile performance is generally solid, staying within acceptable thresholds for load speed and visual stability.
- Reputation: 73% - The brand has a visible social presence and clear customer reviews, but conflicts in location data and a lack of independent press coverage affect its overall authority.
- LLM-Ready Content: 60% - The page is well-structured and recently updated, though it lacks a clear author profile and more descriptive subheadings to fully optimize for AI discovery.
The main takeaway overall
The big picture is that the site is in a good place on the basics, but a few credibility and identity signals aren’t coming through as clearly as they could. None of this reads like a “problem,” it just leaves some important details harder for AI systems to confidently connect and reuse. Next up, we’ll walk through the specific areas where information was missing or inconsistent, organized by section. Once those pieces are clearer, the rest of what you’ve already built has a better shot at showing up consistently in AI-driven results.
Detailed Report
Discoverability
❌ Missing image or video sitemap
What we saw
We didn’t see an image or video sitemap available for the site. For a site with a lot of project imagery, that’s a meaningful piece of content that can be harder to surface without a clear feed.
Why this matters for AI SEO
Generative engines and search systems rely on consistent, well-organized signals to understand what media exists and what it represents. When that media isn’t easy to discover at scale, it can reduce how often images/videos get pulled into AI-driven experiences.
Next step
Publish an image sitemap (and/or video sitemap if relevant) so your project photos and media have a clear discovery path.
Structured Data
❌ Resource/blog page structured data not found
What we saw
We weren’t able to find structured data on the resource/blog page because the resource page file was missing or empty in the evaluation. That meant there was no article-level markup to review.
Why this matters for AI SEO
When content pages don’t provide clear content descriptors, it’s harder for AI systems to confidently classify the page as a reusable “article” and connect it to the rest of your brand footprint. That can limit how often your content is understood and referenced.
Next step
Make sure the resource/blog page is available and includes article-level structured data so the content can be recognized consistently.
❌ No clear author identified for resource/blog content
What we saw
An author couldn’t be identified for the resource/blog content because the resource page wasn’t available to evaluate. As a result, we couldn’t confirm a real, non-generic author signal.
Why this matters for AI SEO
Authorship is a common trust cue for AI systems when they decide whether to quote, summarize, or rely on content. If the author signal isn’t present or can’t be verified, the content may be treated as less attributable.
Next step
Add a clear author attribution on resource/blog content so the author can be consistently identified.
❌ Author profile missing “sameAs” identity links
What we saw
We couldn’t verify any author “sameAs” links because the author couldn’t be identified from the missing resource/blog page. That left no way to confirm author identity connections.
Why this matters for AI SEO
AI systems are more confident when an author can be tied to consistent identity references across the web. Without those connections, it’s harder to disambiguate “who wrote this” and treat the author as a stable entity.
Next step
Once an author is in place, include consistent identity links for that author so attribution is easier to validate.
AI Readiness
❌ No Wikidata entity found for the brand
What we saw
We didn’t see a Wikidata entity connected to the brand during the evaluation. This was called out as one of the bigger gaps in the AI readiness section.
Why this matters for AI SEO
Wikidata is a common reference source used to confirm brand entities and reduce ambiguity. When it’s missing, generative engines may have a harder time consistently anchoring your business to a single, authoritative identity.
Next step
Create or claim a Wikidata entry for the brand so AI systems have a reliable entity reference.
Reputation
❌ Brand identity data is inconsistent across sources
What we saw
We saw a major conflict in identity data across different platforms: some sources report addresses in Salt Lake City and Boca Raton, while the website suggests a Chicagoland focus. That creates an unclear “home base” for the brand.
Why this matters for AI SEO
Generative engines lean on consistent identity details to decide whether multiple mentions are the same entity. When location signals conflict, it can weaken trust and make it harder for AI systems to confidently connect your brand’s references together.
Next step
Standardize the brand’s core identity details (especially address/location) across the key places it appears online.
❌ No Wikidata entity for the brand
What we saw
A Wikidata entity for the brand wasn’t found in the reputation signals review. This aligns with the missing Wikidata connection noted elsewhere in the report.
Why this matters for AI SEO
Without a recognized entity anchor, AI systems have fewer reliable ways to confirm the brand’s identity across different sources. That can limit how strongly your offsite presence reinforces what’s on your site.
Next step
Establish a Wikidata entity for the brand to create a consistent offsite identity anchor.
❌ Missing Wikidata identity anchors
What we saw
Wikidata identity anchors were not present/confirmed for the brand. In practice, that means there wasn’t a stable Wikidata-based reference point to tie back to.
Why this matters for AI SEO
Identity anchors reduce confusion and help generative engines treat the brand as a single, well-defined entity. Without them, brand references can remain more fragile or fragmented.
Next step
Add and verify the brand’s core identity anchors within Wikidata so entity matching is more consistent.
❌ No independent press coverage found
What we saw
We didn’t see independent press mentions in third-party publications noted in the findings. The report did note owned press/releases, but not outside coverage.
Why this matters for AI SEO
Independent third-party mentions act as external confirmation that a brand is notable and trusted beyond its own channels. Without that kind of validation, AI systems may have fewer strong references to pull from.
Next step
Secure a few credible third-party mentions so the brand has stronger independent references online.
LLM-Ready Content (Blog Analysis)
Heads up: this section looks at one article as a snapshot, so it’s a little more interpretive than the rest of the report and may shift slightly from run to run. Have questions? Just shoot us an email at hello@v9digital.com
❌ No non-generic author shown
What we saw
We didn’t see a visible author name or a clear author signal tied to a real person for the resource content. In other words, the content reads as “site-written,” without a specific byline.
Why this matters for AI SEO
Clear authorship helps AI systems attribute information to a credible source, especially for advice-style content. When the author isn’t clear, it can reduce confidence in quoting or summarizing the page.
Next step
Add a clear, non-generic author attribution to the article so the content has an identifiable source.
❌ No table included (bonus)
What we saw
No table element was found in the provided content. That means there wasn’t a compact, structured block summarizing key comparisons or takeaways.
Why this matters for AI SEO
AI systems often pull concise, structured snippets when they’re available because they’re easy to interpret and reuse. Without any structured summary blocks, the content can be slightly harder to extract cleanly.
Next step
Add a simple table where it naturally fits to summarize key options, steps, or comparisons.
❌ Subheadings aren’t descriptive enough
What we saw
The subheadings didn’t consistently describe what the next section is actually about in a way that matches the section’s first sentence. As a result, the section topics are a little harder to identify at a glance.
Why this matters for AI SEO
Generative engines rely heavily on headings to understand content structure and decide what to quote for specific questions. When headings are vague, the model has to work harder to map the right answers to the right queries.
Next step
Rewrite subheadings so each one clearly signals the specific topic covered in the section that follows.
Does Anything Seem Off?
Thanks for taking our free GEO Grader for a spin. When we started this journey, the tool had a fairly long processing time to check everything we wanted both onsite and offsite, so we made a few adjustments on the backend to speed things up. As a result, there are times when the grader may not get everything 100% right. If something feels off, we recommend running the tool a second time to confirm the results. From there, you’re always welcome to reach out to us to schedule a GEO consultation, or to have your SEO provider validate the findings with a more detailed crawl and manual review.
