Visiby is an AI citation intelligence platform that tracks brand share of voice, extracts passage provenance, and generates prioritized optimization briefs across major AI engines.
What the product does and how it is positioned
Visiby is an answer engine optimization and citation intelligence platform developed by FNA Technology. It is designed to help marketing and SEO teams track how generative AI models discover, cite, and recommend their brands compared to competitors.
The platform monitors queries across multiple major AI engines, mapping brand entity perception and attributing citations down to specific page URLs and structural content elements. Through automated weekly analysis, it pairs search engine traffic data with AI visibility trends, generating prioritized remediation plans and content briefs.
Source-supported ways to use the product
Marketing operators monitor brand citation frequency, prompt wins or losses, and descriptive adjective associations across generative search engines.
Content teams review extraction heatmaps to identify whether AI engines prefer tables, FAQ schema, or headings for specific topic clusters.
Technical managers identify missing schema markup, thin content, and indexing blocks that prevent AI systems from parsing and quoting website pages.
The documented workflow, where available
The workspace defines the brand domain, competitive landscape, and the universe of prompts relevant to prospective buyers.
The system runs an overnight intelligence sweep every Tuesday, sampling prompts across five AI engines to track citation shares and page-level extraction.
Teams review the weekly digest, inspect passage provenance, and assign prioritized content briefs ranked by effort and forecast impact.
Visiby evaluates generative model answers through passage-level provenance and structural recipe intelligence. Rather than assessing overall domain authority alone, the platform identifies the exact on-page elements that models reference when formulating answers to user prompts.
Through continuous prompt sampling across multiple AI engines, the software compiles a heatmap showing extraction preferences across content types. Teams can observe whether a particular engine draws information from structured H2 headers, FAQPage schema blocks, tabular comparison matrices, or scannable bullet points.
Checks to run with your own material and workflow
What was checked and when
Answers based on the source-checked product record
Visiby tracks brand presence and citations across ChatGPT, Claude, Perplexity, Gemini, and Google AI Overviews.
Recipe Intelligence is a heatmap feature that tracks which on-page elements, such as H2 headings, FAQ blocks, tables, and lists, AI engines extract to generate answers.
The citability audit identifies issues that affect AI parsing, including pages blocked from indexing, missing OpenGraph tags, thin content under 250 words, and missing schema markup.
Action plans rank recommendations using an effort-by-impact framework that incorporates why-now signals, forecast confidence, dependencies, and attached content briefs.
Visiby executes an automated intelligence run weekly on Tuesday mornings, sending a summary digest and updated briefs directly to the user's inbox.
