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Generative Engine Optimization (GEO)

ChatGPT, Perplexity, Gemini, Claude, and Grok now answer the question your buyers used to type into Google. We make sure they answer it in your favor.

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The first place a buyer learns about you in 2026 is not Google. It is an AI answer.

When a CFO types your firm’s name into Perplexity, or asks Claude “is this the right wealth advisor for a $40M rollover,” the answer they get is the asset that closes or kills the deal. That answer is built from a citation graph — Wikipedia, authoritative coverage, structured data, owned content, and a small handful of provider-favored sources. Generative Engine Optimization is the defense of that citation graph.

The Helios Protocol audits how six frontier engines answer 80 of your buyer’s most-asked questions, maps the source graph each engine pulls from, and runs a 90-day reclaim against the inputs LLMs are measurably sensitive to. We do not promise specific answers — we promise the rehearsal, the source work, and the drift tracking that move the needle.

The four-phase protocol

How an engagement actually runs.

  1. 01

    Baseline & Citation Map

    We run the 80-prompt bank across six LLMs, capture each answer with citations, and map the source graph LLMs actually pull from.

    Days 0–14
  2. 02

    Source Reclaim

    Wikipedia infobox reconciliation, authoritative-outlet placement, structured-data hardening, knowledge-panel alignment.

    Days 14–60
  3. 03

    Correction & Provenance

    Hallucination corrections filed with provider feedback channels. Provenance and authorship signals embedded across owned assets.

    Day 30 →
  4. 04

    Monitoring & Re-rehearsal

    Continuous prompt-bank rehearsal. New answer drift flagged inside 72 hours. Quarterly delta scorecard.

    Day 90 →
Plain-English FAQ

Questions every Generative Engine Optimization (GEO) buyer asks.

Is GEO the new SEO?

Not a replacement — a parallel front. SEO defends your blue links. GEO defends the paragraph above them. As of 2026, roughly 38% of branded queries get answered before the user scrolls — that paragraph is the new home page.

Can you guarantee a specific LLM answer?

No, and avoid anyone who says yes. Frontier models retrain. We work the citation graph and the provenance signal — the inputs LLMs are demonstrably sensitive to — and we measure the answer drift quarterly.

What's the difference between GEO and AI Deepfake Monitoring?

GEO is about how LLMs describe you when asked. Deepfake monitoring is about synthetic media (voice, face, fake interviews) created in your name. Different threat surface, different protocol — most executives need both.

Helios Protocol

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