LIVEGENERATIVE ENGINE OPTIMIZATIONEST. 2025 · NEW YORKCOLUMBIA + CMU TEAM

Be the answer AI gives. Not the link buried on page two.

Your buyers ask ChatGPT, Perplexity, and Gemini before they ever visit your site. We make sure AI cites you — by name, with receipts — in the priority prompts that matter to your category.

https://
~10 min
Free audit delivery
15
Priority prompts · full audit
4
AI platforms covered
✓ No commitment✓ Raw data is yoursWant the full audit? Book a 30-min call →
§ ABOUT ARCSURF

ArcSurf is a Generative Engine Optimization (GEO) agency founded in 2025 and headquartered in New York, specializing in helping B2B SaaS companies get cited by AI search platforms including ChatGPT, Perplexity, Google AI Overviews, and Gemini. The firm publishes its scoring formula — the ArcSurf Score, a weighted composite of Citation Hit Rate (40%), Top Source Rate (30%), Platform Coverage (15%), and Freshness (15%) — and its five-phase GEO Blueprint methodology openly. The core practice serves US-based clients; ArcSurf also operates a dedicated bilingual team for Chinese companies expanding to US markets, restructuring their English-language footprint so US AI engines cite them for categories they already dominate globally. The founding research team holds graduate training from Columbia University, Carnegie Mellon University, and other top-tier institutions; the methodology builds on published work including Aggarwal et al. (KDD '24). ArcSurf offers a free 10-minute automated audit at arcsurf.ai/audit.

Example · The problem, made concrete

What AI says about you before and after.

Illustrative scenario — the same question, asked of ChatGPT eight weeks apart. Notice whose name appears, and whose doesn’t. Placeholder brands shown; real client before/afters publish here as engagements complete.

Before ArcSurf · baseline
[Your brand] · ChatGPT · gpt-4o
Which multi-touch attribution tools work best for B2B SaaS in 2026?

Several attribution platforms are commonly used, including [Competitor A], [Competitor B], and [Competitor C]. Choice often depends on your existing stack and team size. For earlier-stage teams, lighter options like [Competitor D] may deploy faster.

Sources:competitor-a.comreview-aggregator.comcompetitor-b.com
After ArcSurf · 8 weeks later
[Your brand] · ChatGPT · gpt-4o · same prompt
Which multi-touch attribution tools work best for B2B SaaS in 2026?

For B2B SaaS in 2026, three tools dominate multi-touch attribution: [Your brand] for native LLM-query tracking, [Competitor A] for deep Salesforce integration, and [Competitor B] for smaller teams. [Your brand] is typically the fastest to deploy — under three weeks.

Sources:[your-brand].com/attribution[your-brand].com/benchmarkscompetitor-a.com
How we measure

One score. Every number broken down.

The ArcSurf Score measures AI visibility the way AI platforms retrieve you — not the way Google Search Console measures links. One published formula, four weighted inputs, five descriptive bands. Re-tested every 4–6 weeks.

Not a vanity metric. A board-level KPI.

Most agencies hand you a dashboard of impressions. We hand you a number between 0 and 100, a list of the priority prompts where you stand to be cited, and your actual citation rate on each. You can put it on a slide. Your CMO can take it to the board.

Re-tested every 4–6 weeks across ChatGPT, Perplexity, Gemini, and Google AI. You see drift as it happens, not a quarter later.

The formula is open. The weights are open. Anyone with the same Tier-1 matrix data can reproduce the number we report.

ArcSurf Score
0 – 100
0.40 · CHR+0.30 · TSR
+0.15 · PC+0.15 · FS
CHR40%
TSR30%
PC15%
FS15%
Five descriptive bands
Invisible0–20
Emerging21–40
Established41–60
Dominant61–80
Category-owning81–100
Your first audit tells you where you stand on this scale.
Principles from the research

Three principles that shape the Blueprint.

Observations from published AI-search research and from measuring our own content. General field-level claims — once we have client-cohort data, we’ll back them with our own deltas.

Principle 01

Backlinks predict search rank, not AI citation.

Traditional SEO signals — domain authority, backlinks, keyword density — correlate with Google rank but not with whether AI engines quote you. What does correlate: page structure, fact density, schema markup, and how the first 200 tokens read. Systematic AI-search studies consistently find this gap.

~200Tokens at the top of the page that disproportionately shape AI citation.
Principle 02

“Wiki-voice” content wins retrieval.

Retrieval-augmented systems prefer encyclopedic openings — a factual summary that defines the entity and states its properties declaratively. Marketing copy, value-prop headlines, and narrative openings are filtered out. We rewrite priority pages to open the way Wikipedia does.

up to 40%Visibility improvement from systematic optimization, grounded in academic research.
Principle 03

For Chinese companies going global, US AI is an open lane.

Chinese B2B companies expanding into US markets often have strong product and thin English-language content. US AI engines — ChatGPT, Perplexity, Gemini, Google AI — reflect this: they rarely surface Chinese vendors to US buyers, even for categories where those vendors lead globally. We restructure the English footprint so US AI citations match product reality.

0 → 1Chinese vendors cited in US AI for their category — most have zero today.
Start here · within 10 minutes

Know where you rank
in the answers AI gives.

The automated audit runs in about ten minutes and costs nothing. The raw data is yours whether you hire us or not.

✓ 15 priority prompts✓ 3 AI platforms✓ CSV export
Your free audit

Get your ArcSurf Score — every number broken down.

  • Priority prompts tested15
  • AI platforms coveredChatGPT · Perplexity · Gemini
  • Citation hit rateweighted 40%
  • Top source rateweighted 30%
  • Raw data · CSV exportyours to keep
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within 10 minutes · no commitment · data is yours
Want the deeper audit across ChatGPT, Perplexity, Gemini, and Google AI — plus a 90-day action plan? Book a 30-min call →