mcp

NeverRanked is a research engagement that measures what AI answer engines cite for a category. The output is a forensic memo plus a prepped punch list for the customer's team to execute against.

This repository holds the marketing site, the dashboard worker source (under dashboard/), and the historical artifacts from the company's prior product.

What this company was, and what it is now

Until May 2026, NeverRanked sold a JavaScript snippet that was claimed to drive AI citations. We ran a pre-registered kill test against our own domain. The result was zero citations. The LLM crawlers do not execute JavaScript, so the snippet was structurally invisible to them.

We stopped selling that product, retracted the public content that promoted it, and rebuilt the company around the measurement layer that does work.

This repository contains both states: the current honest surfaces (homepage, About, ASB pitch, terms, privacy, llms.txt) and the historical artifacts (retired blog posts, retired case studies, retired audits, retired explainers). Anything that contradicts the retraction is either replaced with an honest holder or marked as retired in place.

For the current state of every code path, see ~/.claude/projects/-Users-lanceroylo-Desktop-neverranked/memory/code_rewrite_status_2026-05-21.md in Lance's local Claude memory.

What we measure now

Seven AI surfaces, every day.

• Five citation-grade engines that search the live web and cite their sources: Perplexity, ChatGPT search, Gemini grounded, Microsoft Copilot via Bing, Google AI Overviews.
• Two model-knowledge engines that answer purely from training data: Claude, Gemma.

Both layers measure different failure modes. A brand invisible in citation is invisible when AI fact-checks itself. A brand invisible in model knowledge is invisible at the baseline, before any search happens.

What we deliver

A forensic memo plus a prepped punch list. Per query, per engine, per competitor, per source type. Daily measurement. Monthly delta memo on ongoing engagements.

We do not execute. No content writing, no website edits, no schema deploys, no profile updates. The labor stays with the customer's team or their agency. That separation is structural.

Pricing

• $4,500 kickoff per category. One time.
• $1,500 per month per category, ongoing.
• Per category, not per client.

This is a research engagement, not a SaaS subscription. There is no self-serve dashboard.

Repository layout (current)

neverranked/
├── index.html              honest homepage holder
├── about/, terms/,         current honest pages
│   privacy/, thanks/
├── pitch/asb-hawaii/       current direct-buyer pitch shape
├── pitch/*/                retired pitch pages (holder)
├── blog/, case-studies/,   retired catalogs (holders + noindex)
│   profile/, state-of-aeo/
├── standards/, schemas/,   retired surfaces (holders)
│   agencies/, security/,
│   for-agencies/,
│   principles/, kit/
├── meetings/kits/          current meeting prep, demo bundle
├── dashboard/              app.neverranked.com Worker source
├── llms.txt                rewritten for current state
└── sitemap.xml             homepage only

The historical artifacts (retired pages, audit documents under /audits/, prior explainers like EXPLAINER.md and AGENCY-EXPLAINER.md, the original audit template under /audit-template/) reflect the prior product premise and are preserved for diff context but should not be acted on as current guidance.

Contact

[email protected]