The Silicon Valley AI Visibility Index — 25 Brands Ranked by AI Search Presence

We audited 25 Silicon Valley AI and SaaS companies for AI search visibility. The average score is 62 out of 100. Only 3 brands — Stripe, Perplexity AI, and OpenAI — scored above 88. The other 22 are missing at least one critical technical signal that keeps them partially invisible to ChatGPT, Gemini, and Perplexity when users ask about their category. Here is the full ranking.

How we built the index#

BrandCited is an AI visibility intelligence platform that monitors AI platforms for brand citations and shows you exactly what to fix to appear more often in AI-generated answers. For this index, BrandCited applied a 6-signal technical audit to each of the 25 domains. The signals are: presence of an llms.txt file, AI crawler access rules in robots.txt, Organization schema markup on the homepage, homepage accessibility (HTTP 200 response), a populated meta description tag, and homepage content depth above 300 words. Each signal contributes a fixed point value to the overall quick-scan score (maximum 100).

The top 10 and bottom 5 brands were selected for full BrandCited platform audits covering 30+ signals across five categories: Crawler Access, Structured Data, Content Quality, Trust and Authority, and Technical. All 25 brands received the 6-signal quick scan. For the middle 10, quick-scan scores are marked as estimated in the table below. Full audit details for the top 10 and bottom 5 are shown in the deep-dive sections.

Sources used to identify the 25 brands: YC company directory, Crunchbase Silicon Valley startup search, a16z portfolio, TechCrunch Startup Battlefield alumni, and Sifted US coverage.

What the Silicon Valley AI Visibility Index found#

• Only 3 of 25 brands (12%) scored above 88 out of 100 — the threshold BrandCited associates with consistent AI search citations across ChatGPT, Gemini, and Perplexity.
• 84% of brands (21 of 25) are missing an `llms.txt` file — the AI-specific discoverability file that tells crawlers who you are, what you do, and which content matters. This is the single most common gap across the entire index.
• 60% of brands (15 of 25) have no Organization schema markup on their homepage — meaning AI models cannot definitively resolve their entity identity without relying on partial text inference.
• The average score across all 25 brands was 62 out of 100, compared to a global cross-industry benchmark of approximately 35 out of 100 — Silicon Valley outperforms the global average, but trails what you would expect from companies that build AI products.
• The most striking pattern: companies that build AI tools rank no better on AI visibility than the average SaaS brand. Vectara builds enterprise RAG systems and scores 55. Arize AI monitors LLM performance and scores 55. Writer builds AI content tools and scores 80 — but is missing the llms.txt file that would put it in the top tier.

The full Silicon Valley AI Visibility Index ranking#

Brands marked "est." received a quick 6-signal audit. Run a free full audit at brandcited.ai to see your complete score across all 30+ signals.

What the top Silicon Valley brands are doing right#

Stripe scores 100 out of 100 — the only brand in this index that passes every signal. Stripe published an llms.txt file early in the adoption curve, ahead of most companies in every industry. The file sits at stripe.com/llms.txt and declares what Stripe is, what it does, and which content pages carry the most authority. Their robots.txt explicitly allows GPTBot, ClaudeBot, PerplexityBot, and GoogleExtended. Organization schema with sameAs links to their verified social profiles is present on the homepage. Stripe treats its website as infrastructure. The AI visibility setup is not an accident — it reflects the same engineering discipline that drives everything else the company ships.

Perplexity AI also scores 100 out of 100, which is less surprising when you consider their product. Perplexity builds an AI search engine. They understand exactly which signals determine whether a brand gets cited in AI-generated answers — because they built the system that checks those signals. Their robots.txt allows all major AI crawlers including their own PerplexityBot, GPTBot, ClaudeBot, and Bingbot. Organization schema is present. Their homepage content is structured for extraction, not just for human readers. Perplexity practices what their product teaches.

OpenAI scores 90 out of 100. They lose 10 points for partial AI crawler restrictions in their robots.txt — certain paths are blocked for specific bots, which is a reasonable content protection decision but reduces their overall crawler access score. They gain full marks on everything else: llms.txt is present, Organization schema is in place, homepage content depth is strong, and their meta description is populated. OpenAI's near-perfect score reflects the same understanding that earned Perplexity its 100 — they built the platforms that read this data.

The most common AI visibility gaps in Silicon Valley#

llms.txt is a plain-text file hosted at the root of a domain — yourdomain.com/llms.txt — that tells AI models what your company is, what it does, and which pages carry the most authoritative content. It is to AI models what robots.txt is to search crawlers, except it is about understanding rather than access control.

Of the 25 brands in this index, only Stripe, Perplexity AI, OpenAI, and LangChain have one. The other 21 are leaving AI models to infer their entity identity from page text alone — a process that produces inconsistent results across ChatGPT, Gemini, and Perplexity.

Here is a minimal llms.txt template any company can deploy today:

# llms.txt for [Company Name]

## About
[Company Name] is a [one-sentence description: what you are, what you do, who you serve].

## Key pages
- Homepage: https://[yourdomain.com]/ — overview of the product
- Product: https://[yourdomain.com]/product — feature details
- Pricing: https://[yourdomain.com]/pricing — plan and pricing information
- Blog: https://[yourdomain.com]/blog — AI visibility guides and research

## What we do
[2-3 sentences describing the product in direct, factual language. No marketing copy. AI models use this text to answer questions about your company.]

Hosting this file at yourdomain.com/llms.txt takes 15 minutes. BrandCited checks for it as one of the first signals in every audit.

Organization schema is a JSON-LD block on the homepage that tells AI models — and Google's Knowledge Graph — who you are as a structured entity. Without it, an AI model encountering "Arize AI" or "Vectara" in crawled content has no structured declaration to anchor its understanding. It builds an inference instead, which may be incomplete, inconsistent across platforms, or contaminated by similar company names.

The fix is a single JSON-LD script tag on every page via the site layout:

{
  "@context": "https://schema.org",
  "@type": "Organization",
  "name": "Your Company Name",
  "url": "https://yourdomain.com",
  "description": "One sentence: what you are and what you do.",
  "foundingDate": "2022",
  "sameAs": [
    "https://linkedin.com/company/your-company",
    "https://twitter.com/yourhandle"
  ]
}

The sameAs array links AI models across multiple data sources to the same entity. LinkedIn and Twitter profiles are the minimum. Add your Crunchbase profile if it exists. BrandCited's audits show that Organization schema is one of the highest-impact single fixes for brands scoring below 70 — it moves the needle faster than almost any other change.

Seven brands in this index — Glean, Mem, Orby AI, Kapa AI, Magic, Kolena, and Credal AI — have homepages with fewer than 300 words of visible text. AI models extract entity descriptions from page content. A homepage with 80 words of copy and three feature tiles gives a language model almost nothing to work with.

This does not mean building a long-form homepage. It means making sure the homepage answers five questions in plain text that AI models can extract:

1. 1What is this company?
2. 2What does it do specifically?
3. 3Who does it serve?
4. 4What problem does it solve?
5. 5What makes it different?

A homepage that answers these five questions in 300-500 words of structured prose will pass the content depth signal. Padding with testimonials or feature grids does not help — AI models extract semantic meaning from prose, not layout elements.

How does your brand rank?#

We audited 25 Silicon Valley brands. If yours is not on the list — or if it received an estimated score — run a free full audit at brandcited.ai. BrandCited checks 30+ signals across five categories and shows you your complete score in 30 seconds, with every issue ranked by impact.

The brands that scored best in this index share one trait: they treat AI discoverability as infrastructure, not marketing. Stripe did not publish llms.txt to rank in a leaderboard. They published it because they understand that AI models are now a distribution layer, and distribution layers need to be fed structured data.

The brands that scored lowest are not bad companies with bad products. They are good companies that have not yet treated their website as a machine-readable entity declaration. That is a fixable problem.

Run a free AI visibility audit at brandcited.ai. Your score across 9 AI platforms in 30 seconds, every issue ranked by impact.

Frequently asked questions#

AI visibility measures how often and how accurately AI platforms like ChatGPT, Perplexity, and Google AI Overviews mention your brand when answering relevant queries. For Silicon Valley companies, this matters because their target customers — developers, enterprise buyers, and technical decision-makers — increasingly use AI search tools to research products before visiting a website. BrandCited tracks AI visibility across 9 platforms and shows brands exactly which signals are missing.

Building AI products does not automatically mean your own website is optimized for AI search engines. The signals that matter — llms.txt, Organization schema, AI crawler access in robots.txt — require deliberate implementation decisions that are separate from the AI features in your product. Vectara builds enterprise RAG and scores 55 out of 100. Arize AI monitors LLM performance and scores 55. The gap is not technical capability; it is attention.

SEO optimizes for Google's ranking algorithm, which weights backlinks, content freshness, and user engagement signals. AI visibility optimizes for how AI models like ChatGPT and Perplexity understand and cite your brand. The two overlap — both reward clear content structure and authoritative sourcing — but diverge on specifics. SEO does not require llms.txt or Organization schema. AI visibility does. BrandCited measures both in its audits and shows which gaps affect which platforms.

Add Organization schema JSON-LD to your homepage layout. This single change addresses the most common gap — 60% of brands in this index are missing it — and takes a developer less than an hour to implement. The second fastest fix is publishing an llms.txt file at your domain root. Both changes are verifiable immediately and BrandCited checks both in the first 30 seconds of every audit.

Manual monitoring — typing your brand name into ChatGPT and Perplexity and recording what comes back — gives you a spot check on one or two platforms. BrandCited automates this across 9 AI platforms, runs it continuously, and shows you citation rates, competitor comparisons, and a ranked list of technical fixes. Manual monitoring takes hours per week and misses platform-specific citation patterns. BrandCited surfaces those patterns automatically.

ChatGPT's web browsing feature (used in ChatGPT Plus and Copilot) indexes content from Bing. Submit your sitemap to Bing Webmaster Tools and ensure GPTBot is not blocked in your robots.txt. For ChatGPT's training data, publish structured, authoritative content with clear entity definitions, and add Organization schema to your homepage so the model can resolve your brand as a verified entity. BrandCited checks all of these signals in its full audit.