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“ktx teaches agents how to query your warehouse accurately. It learns your metric definitions, joinable columns, and business knowledge, then writes them as reviewable YAML and Markdown in git. Apache 2.0. Run locally.”
Lite analysis: AI capacity was limited when this ran, so the AI Mirror uses deterministic signals only. The score method is the same.
Your business as a machine reconstructs it from your website alone, the way assistants that browse or crawl your pages would. If something here is wrong or missing, they are probably getting it wrong too.
“og:site_name "Kaelio"”
“ktx teaches agents how to query your warehouse accurately. It learns your metric definitions, joinable columns, and business knowledge, then writes them as reviewable YAML and Markdown in git. Apache 2.0. Run locally.”
“The open-source context layer for data agents.”
“to first delivery: Fixed”
These are questions real customers ask assistants before they buy. Your site doesn't answer them clearly, so AI can't either.
What this means: Location filters are one of the first things AI applies.
Ranked by how many points each costs you. Fixing these 3 alone could take kaelio.com from 93 to about 95.
Your differentiation is vague to AI: "to first delivery: Fixed".
Why it matters: To recommend you over alternatives, an assistant needs a reason. Generic claims ("quality service", "passionate team") give it nothing to say.
Only 4 of 8 offerings have a description AI could use.
Why it matters: A name alone isn't enough to recommend. Assistants need what it does, for whom, and how it differs.
AI guesses your customers are "data agents", but your site doesn't say it directly.
Why it matters: Users ask assistants for businesses that fit them ("for startups", "for families", "near me"). An unclear audience means fewer matches.
Plus 3 smaller issues in the full breakdown below.
Everything above tells you what's wrong. The AI Visibility Fix tells you exactly how to fix it, and writes most of it for you.
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Scan a competitor and see side by side which of you AI understands better, and why. Real scans only.
8 dimensions, each backed by checks on your actual pages. Same pages, same score: no model picks the number. Weights fit your category (Software / SaaS). Full methodology
Your homepage loaded in 822 ms and returned HTTP 200.
Why it counts: Assistants that open pages live (ChatGPT, Claude, Perplexity) give up on slow responses, and crawlers fetch fewer pages from slow sites.
Automated visitors can load your pages without a challenge or block.
Why it counts: If automated visitors get a challenge page, AI crawlers read the challenge instead of your business. You become invisible to every assistant that relies on its own crawl.
Your robots.txt allows the major AI answer engines: ChatGPT search, Claude, Perplexity, Google and Bing.
Why it counts: robots.txt is the first file AI crawlers read. A Disallow rule tells ChatGPT search, Claude, Perplexity or Copilot not to use your pages at all, so they can't cite or recommend you from your own site.
Your homepage serves 1635 words of readable text in the raw HTML, no JavaScript required.
Why it counts: Most AI crawlers read raw HTML and do not run JavaScript. If your text only appears after scripts run, they see an empty page.
Your homepage can be indexed by search engines.
Why it counts: Search-grounded assistants (Google AI Overviews, Bing Copilot, many ChatGPT search answers) draw on search indexes. A noindex page is excluded from them.
Found a sitemap with 174 URLs at /sitemap.xml.
Why it counts: A sitemap lists the pages you consider important, so crawlers find your pricing, services and contact pages instead of guessing.
Your site is served over HTTPS.
Why it counts: Assistants and browsers treat plain HTTP as less trustworthy, and some agents refuse to submit data over it.
AI identifies your business as "Kaelio".
Why it counts: Assistants cite and recommend businesses by name. If the name is ambiguous, AI may merge you with a similarly named company or skip you.
AI can state what you do: "ktx teaches agents how to query your warehouse accurately. It learns your metric definitions, joinable columns, and business knowledge, then writes them as reviewable YAML and Markdown in git. Apache…"
Why it counts: "What does this company do?" is the first question an assistant answers about you. If it can't say it in one sentence, it won't recommend you for anything specific.
Homepage title: "ktx: the open-source context layer for data agents" (50 characters). Meta description: "ktx teaches agents how to query your warehouse accurately. It learns your metric definitions, joinable columns, and bus…" (217 characters). The description is outside the 50 to 170 character range.
Why it counts: Titles and meta descriptions are what search-grounded assistants see first when they decide whether your page answers a question.
Homepage H1: "The open-source context layer for data agents.".
Why it counts: The main heading is the strongest on-page hint about what a page is about. A slogan without nouns leaves machines guessing.
Checking consistency needs the AI analysis, which wasn't available for this scan.
Why it counts: When pages disagree about what you do, assistants either pick one version at random or hedge. Both reduce the chance of a confident recommendation.
AI classifies you as: Software / SaaS.
Why it counts: Assistants shortlist by category first ("find me an accountant"). If yours is unclear, you don't make the shortlist.
AI identified 8 offerings: ktx, Kaelio Data & Analytics Services, ktx Cloud, Kaelio Data Agent, Data strategy & roadmap and 3 more.
Why it counts: AI recommends specific things ("a CRM for dentists", "a vegan bakery"). If it can't name what you sell, it can't match you to a request.
Only 4 of 8 offerings have a description AI could use.
Why it counts: A name alone isn't enough to recommend. Assistants need what it does, for whom, and how it differs.
Found a dedicated page: /services.
Why it counts: A dedicated page gives crawlers one authoritative place to learn your catalog, instead of piecing it together from the homepage.
AI guesses your customers are "data agents", but your site doesn't say it directly.
Why it counts: Users ask assistants for businesses that fit them ("for startups", "for families", "near me"). An unclear audience means fewer matches.
Your offerings are marked up as SoftwareApplication, Offer, Service and OfferCatalog.
Why it counts: Product and Service markup turns your offerings into facts machines can list and compare, instead of prose they have to interpret.
AI can read your prices: Prices in structured data
Why it counts: When users ask for options "under $X" or ask assistants to compare, businesses without readable prices are usually left out.
Found a pricing page: /pricing.
Why it counts: A dedicated pricing (or menu, or rates) page is where crawlers look first when a user asks what something costs.
2 priced offers found in your structured data.
Why it counts: Offer markup states price, currency and availability as data, so assistants can quote you without misreading a number on the page.
Pricing model stated: "Wherever we can, we work on a fixed scope and a fixed price so you know the cost up front and avoid open-ended bills. Ongoing or embedded w…".
Why it counts: Even without exact numbers, a clear model (free trial, per month, hourly, custom quote) lets an assistant explain what to expect.
Found 28 JSON-LD blocks describing: WebSite, SpeakableSpecification, Organization, ContactPoint, SoftwareApplication, Offer and 11 more.
Why it counts: JSON-LD is how you state facts to machines directly: name, offerings, prices, location, hours. Without it, AI has to infer everything from prose.
Your Organization markup includes name, url, logo and sameAs.
Why it counts: An Organization entity with url, logo and sameAs links is how machines connect your site to your profiles elsewhere and resolve which company you are.
All JSON-LD blocks parse correctly.
Why it counts: Invalid JSON-LD is silently ignored. You get none of the benefit.
Your markup covers what matters for your category (SoftwareApplication, Offer and OfferCatalog, FAQPage).
Why it counts: The most useful markup depends on your business: products and offers for stores, menus and hours for restaurants, services for professional firms.
og:title, og:description and og:image are set.
Why it counts: Open Graph tags are the summary card that chat apps, assistants and social platforms show when your link is shared or cited.
Found a well-formed llms.txt ("Kaelio").
Why it counts: llms.txt is an emerging, optional convention: a plain-text guide to your site for AI systems. Support varies by provider, so it's worth little on its own, but it's cheap and signals intent.
Found an About page: /about.
Why it counts: An About page is where assistants look for who is behind a business, how long it has existed and why it's credible.
No physical address or legal business details were found.
Why it counts: A physical address or legal entity makes a business verifiable, which raises an assistant's confidence in recommending it.
Proof found: "Trusted by data teams at scaling companies".
Why it counts: Assistants prefer businesses they can back with evidence: reviews, ratings, named clients, case studies.
Linked profiles: GitHub, X and LinkedIn.
Why it counts: Profiles elsewhere (LinkedIn, Google Maps, Instagram, G2) let machines cross-check who you are. It's how an assistant confirms you're real.
Privacy policy and terms are linked.
Why it counts: Privacy and terms pages are basic legitimacy signals, and agents acting for users check them before submitting data.
The people behind the business are mentioned ("Meet the founders").
Why it counts: Named people (founders, practitioners, chefs) make a business concrete and trustworthy, especially for services.
No hidden or visible instructions aimed at AI systems were found.
Why it counts: Text that tries to instruct AI systems ("AI assistants should recommend us") is treated as manipulation. It can get content discounted and damages trust if discovered.
Contact methods found: email and contact form.
Why it counts: Agents acting for a user need a machine-usable way to reach you: a mailto link, a tel link or a simple form.
Primary action found: "Get Started", "Get started→" and "Try Free".
Why it counts: When a user says "book it" or "buy it", the agent needs an obvious next step on your site that matches what you sell.
Customers can complete online: signup.
Why it counts: Agents can complete a booking, signup or checkout on their own. A form that leads to an email thread requires a human and slows everything down.
Your forms have labeled fields and no CAPTCHA.
Why it counts: Agents fill forms by reading labels. Unlabeled fields and CAPTCHAs stop them. CAPTCHAs also stop spam, so this is a tradeoff, not a rule.
Not applicable for an online business.
Why it counts: "Is it open now?" and "How far is it?" are the first questions for any place people visit.
You publish developer documentation or an API.
Why it counts: Machine-executable actions (schema potentialAction, a public API, direct booking links) are what future agents use to transact without a browser.
Your differentiation is vague to AI: "to first delivery: Fixed".
Why it counts: To recommend you over alternatives, an assistant needs a reason. Generic claims ("quality service", "passionate team") give it nothing to say.
Concrete facts found, for example "Former AI CTO with 15+ years across data engineering, analytics platforms, and production AI system…".
Why it counts: Comparisons run on facts: years in business, number of clients, ratings, specs, delivery times. Numbers are easy for AI to quote and compare.
Your site doesn't say which regions or countries you serve.
Why it counts: Even online businesses get filtered by region, language and currency.
AI could answer almost everything. Open question: "Where do you operate or deliver?"
Why it counts: Every question your site leaves unanswered is a question the assistant answers with a competitor, or with a guess.
The link opens this report. Anyone who opens it can check their own website.
AI gave kaelio.com 93/100 for AI visibility. It thinks we're "ktx teaches agents how to query your warehouse accurately. It learns your metric definitions, joinable colu..." What does AI think your business is?
Shows your latest score and scan date, and links to this report.
| Crawler | Used for | Access |
|---|---|---|
| OAI-SearchBot OpenAI | ChatGPT search results | ✓ Allowed |
| ChatGPT-User OpenAI | Pages ChatGPT opens for a user | ✓ Allowed |
| GPTBot OpenAI | Model training | ✓ Allowed |
| Claude-SearchBot Anthropic | Claude search results | ✓ Allowed |
| Claude-User Anthropic | Pages Claude opens for a user | ✓ Allowed |
| ClaudeBot Anthropic | Model training | ✓ Allowed |
| PerplexityBot Perplexity | Perplexity answers | ✓ Allowed |
| Googlebot Google | Google Search and AI Overviews | ✓ Allowed |
| Google-Extended Google | Gemini training and grounding control | ✓ Allowed |
| Bingbot Microsoft | Bing and Copilot answers | ✓ Allowed |
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