venust.ai
Finalizing the report
Preparing the stored Is Agentic score
Essential—
Recommended—
Bonus signals—
venust.ai
Preparing the stored Is Agentic score
venust.ai
These checks describe whether an ordinary agent can enter, read, and operate the public site.
Agents can reach the site
Crawler access and bot defenses.
Core content is available
Useful content remains accessible without a fragile browser-only path.
Navigation fails safely
Redirects and missing pages give agents a recoverable path.
Controls are understandable
Forms and interactive controls expose usable names and structure.
The public website is always evaluated. Optional surfaces appear when the scan finds positive evidence that they apply.
Strong
Weighted across 16 applicable checks
Critical access gaps come first, followed by other applicable readiness gaps.
Make sure a clean search for your brand name returns your own domain in the top results. If it does not, your brand may be too generic, conflict with a more established term, or not yet indexed. Strengthen brand-name search by claiming consistent NAP across listings, earning press mentions that link to the canonical domain, and avoiding redirect chains that mask the apex domain in search results.
Checks are grouped by relevance for Business sites.
8717 chars, semantic headings (1 H1 + 10 H2s + 15 H3s), 11.5% content ratio
Site accessible to 6 AI agent user-agents
No meta-refresh stubs, JavaScript-redirect stubs, or cross-domain hops across 6 checked pages
All 5 sampled pages are publicly readable (5 with substantive content)
Canonical URL serves text/markdown and text/html via Accept negotiation with Vary: Accept
All major AI crawlers can reach the site: ChatGPT-User, ClaudeBot, Google-Extended, ora-agent, DeepSeekBot.
Nonexistent paths return HTTP 404 with markdown guidance for agents - the strongest 404 contract
venust.ai appears once in brand-name search results for "VenustAI" (position #4 out of 10)
How to pass
Make sure a clean search for your brand name returns your own domain in the top results. If it does not, your brand may be too generic, conflict with a more established term, or not yet indexed. Strengthen brand-name search by claiming consistent NAP across listings, earning press mentions that link to the canonical domain, and avoiding redirect chains that mask the apex domain in search results.
Valid sitemap found at https://venust.ai/sitemap.xml with 49 entries
Rich JSON-LD identity: Organization with name, description, url, and sameAs/logo/address (2 blocks)
All metadata signals present: canonical URL, lang="en", og:image, og:type
Organization schema complete with contactPoint and address
All trust anchor pages verified: About, Contact, Privacy
All 6 measured pages fit an agent context budget (largest ~2K tokens)
MCP server at https://api.venust.ai/mcp - consider adding /.well-known/mcp for standard discovery
How to pass
Serve your MCP server at /.well-known/mcp, publish a server-card.json at /.well-known/mcp/server-card.json, or reference it in llms.txt so agents can discover it automatically without manual URL input.
Found the llms.txt at https://venust.ai/llms.txt.
The llms.txt is well-formatted: 24 lines with markdown links, 1,806 characters in total.
Pricing structured data (schema.org/Offer) found
Entity linking to linkedin.com - add more authority profiles (Wikipedia, Wikidata, LinkedIn, GitHub)
How to pass
Add sameAs links in your JSON-LD structured data pointing to your Wikipedia page, Wikidata entry, GitHub org, and social profiles. This helps AI disambiguate your brand from similarly named entities.
Some extended schema types found: ProfessionalService, FAQPage - add FAQPage, Service, or AggregateRating for full coverage
How to pass
Expand your JSON-LD beyond Organization/WebSite. Add FAQPage for common questions, Service or Product for offerings, AggregateRating or Review for social proof, and BreadcrumbList for navigation context.
All 5 probed llms.txt links resolve to real content
Code fences balanced across 1 markdown document
Returns markdown when requested via Accept header
API returns JSON error responses (403 at https://api.venust.ai)
Server HTML is a well-structured document (main=true, landmarks=4/4, h1=1, maxHeadingSkip=1).
82 native controls, 0 non-native div-soup affordances (100% native).
82/82 interactive elements have a computable accessible name (100%).
3/3 form controls have an associated label (100%).
No hidden instruction text detected in accessibility-tree attributes or off-screen content.
What does venust.ai do and who is it for? Explain it back to me.
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Source: Ora API
What does venust.ai do and who is it for? Explain it back to me.
5 steps1 reasoning step
Agent successfully retrieved and synthesized the core information about VenustAI's services, positioning, and pricing model directly from the homepage. The site is moderately navigable for discovery but forces visitors to contact sales for pricing details; the agent had to flag missing technical specificity and team transparency as confusing gaps rather than discovering them as hidden content.