What is generative engine optimization (GEO)?

Generative engine optimization (GEO) is the practice of optimizing content so AI answer engines such as ChatGPT, Claude, and Gemini cite your brand when buyers ask buying-stage questions. SignalMint measures where you are missing from those answers and generates briefs to close the gap.

How do I know if AI search engines cite my competitors instead of me?

SignalMint probes Claude, ChatGPT, and Gemini with your buyers' real questions across four funnel stages, flags every query where a competitor is cited and your brand is not, and scores each gap 0-100 by urgency.

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Find where AI search ignores your brand

SignalMint probes Claude, ChatGPT, and Gemini with your buyers' real questions, scores each citation gap by urgency 0–100, and generates CMS-ready content briefs to close them.

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signalmint — gap report

# Gap Detector output — sorted by urgency

GAP #1 score: 87/100 · competitive

query: "best B2B ABM platform 2026"

brand cited: NO · competitor: Demandbase (4 engines)

→ Brief queued for generation

GAP #2 score: 72/100 · evaluation

query: "AEM personalization tools enterprise"

brand cited: NO · competitor: Mutiny (3 engines)

→ Brief queued for generation

# Brief Generator — writing content

✓ BLUF answer generated (2 sentences)

✓ FAQ block: 6 Q&As · 80 words each

✓ FAQPage JSON-LD + Article schema

✓ Brief saved → ready for your CMS

signalmint@pipeline ~$

Three-agent pipeline

How SignalMint works

AGT 1

Query Runner Agent

Probes Claude, ChatGPT, and Gemini with buying-stage queries built from your brand profile — category, ICP, and competitor list — across four stages: awareness, consideration, evaluation, and competitive. Records full response, brand mention flag, competitor mentions, and sentiment. Runs all three engines in parallel with bounded concurrency.

Anthropic API · OpenAI API · Google Gemini API

AGT 2

Gap Detector Agent

Analyses query results and scores each citation gap 0–100 using a weighted urgency formula: priority weight (high=40, medium=25, low=10), stage weight (late_stage=20, competitive=18, evaluation=15), competitive gap bonus (+30 when competitor cited without brand), multi-engine penalty (+5 per additional engine miss).

Weighted scoring · Competitor exposure report · JSON output

AGT 3

Brief Generator Agent

Uses Claude to generate a structured content brief for each top-ranked gap: a BLUF answer (2–3 sentences AI can cite directly), FAQ block (5–8 questions with 80-word answers), FAQPage JSON-LD schema, and Article JSON-LD schema. Briefs are saved to your dashboard ready to copy into any CMS.

Claude (Anthropic API) · Supabase · Inngest

Sample output

What a gap report looks like

QUERY	STAGE	URGENCY SCORE	ENGINES MISSING	COMPETITOR CITED
"best B2B ABM platform 2026"	competitive	87/100	ChatGPTClaudeGemini	Demandbase
"AEM personalization enterprise 2026"	evaluation	72/100	ClaudeGemini	Mutiny
"how to reduce content flicker personalization"	consideration	54/100	GeminiChatGPT	Optimizely
"GEO content optimisation for B2B"	awareness	31/100	Claude	—