Chatoptic Introduces Paragraph-Level Citation Intelligence and Query Fan-Out Analysis to Transform AI Visibility Tracking

Chatoptic announces its most significant AI Visibility product update to date, introducing paragraph-level citation intelligence, cross-model query fan-out visibility, citation aggregation reports, and advanced competitive filtering. The new features enable brands to understand exactly how AI-generated answers are constructed and how to strategically influence their positioning across major language models.
Tel Aviv, ISRAEL - February 18, 2026 - Chatoptic, an AI visibility tool [https://www.chatoptic.com/] for Generative Engine Optimization (GEO), today announced a major product update that introduces paragraph-level citation intelligence, cross-model query fan-out visibility, and AI visibility segmentation across tracked prompts.

The update is designed to give brands a clearer understanding of how AI-generated answers are constructed and which external sources influence them.

AI-generated answers are rapidly becoming a primary discovery layer for consumers. According to Reuters (February 2025), ChatGPT alone surpassed 800 million weekly active users, signaling a fundamental shift in how users search, compare, and evaluate brands.

Understanding How AI Answers Are Built

Large Language Models such as ChatGPT, Gemini, Claude, and Perplexity increasingly generate answers by retrieving and synthesizing information from external web sources.

Until now, most visibility tools showed only which URLs were cited at a general level.

Chatoptic now maps which specific sources influence each paragraph and sentence within AI-generated answers.

This allows brands to identify:

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Which sources shape the framing of answers

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Which narratives dominate across personas

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Where competitors are influencing positioning

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Which external sources repeatedly impact answer construction

Instead of tracking citations as a flat list, brands can now see narrative influence at a granular level.

Cross-Model Query Fan-Out Visibility

When AI models trigger web search, a single user prompt is often split into multiple sub-queries, a process commonly referred to as Query Fan-Out.

Chatoptic now makes these sub-queries visible across supported AI models.

Brands can:

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See how a main prompt is decomposed into subtopics

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Identify the specific search terms driving content retrieval

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Optimize content around actual sub-query structures rather than guessing intent

By aligning content with these sub-queries, brands increase their likelihood of being selected and cited in AI-generated answers.

Aggregated Citation Intelligence and Competitive Gap Detection

Chatoptic has also introduced a new Citations Report that aggregates citation data across all tracked prompts.

The report enables brands to:

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Detect recurring citation sources

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Identify dominant content types influencing AI answers

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Analyze competitor presence at scale

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Spot brand mention gaps in sources already shaping AI responses

For example, if competitors are mentioned in industry blogs, YouTube videos, or news articles that AI models frequently cite, brands can strategically engage in those sources to improve future inclusion.

AI Visibility Segmentation by Topic

Instead of relying on a single aggregated visibility score, Chatoptic now allows prompt tagging and AI visibility segmentation by product, service, feature, or topic.

This enables marketing teams to:

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Identify strengths and weaknesses across thematic areas

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Align reporting with internal business units

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Prioritize optimization efforts based on real visibility gaps

A Shift from Tracking Mentions to Understanding Influence

The impact of AI-generated answers extends beyond information retrieval. Recent data from McKinsey (October 2025) indicates that around 50% of consumers already use AI-powered search tools when researching products and services, underscoring the growing role of AI-generated answers in shaping brand perception and purchase decisions.

According to Pavel Israelsky, Co-Founder of Chatoptic:

"AI visibility is no longer about counting citations. It is about understanding how answers are constructed and where narrative influence originates. When you know which sources shape each paragraph and which sub-queries drive retrieval, you can intervene strategically".

About Chatoptic

Chatoptic is an AI visibility tool for Generative Engine Optimization (GEO), that helps brands understand how they appear in AI-generated answers across large language models such as ChatGPT, Gemini, Claude, Perplexity and others. The platform enables persona-based visibility tracking, citation intelligence analysis, competitive gap detection, and LLM-friendly content generation aligned with AI retrieval patterns.

For more information or to request a live demo, visit: https://www.chatoptic.com

Media Contact
Company Name: Chatoptic
Contact Person: Pavel Israelsky
Email:Send Email [https://www.abnewswire.com/email_contact_us.php?pr=chatoptic-introduces-paragraphlevel-citation-intelligence-and-query-fanout-analysis-to-transform-ai-visibility-tracking]
Country: Israel
Website: https://www.chatoptic.com/

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This release was published on openPR.