Myrah is an AI visibility platform that shows how large language models describe, compare, and cite a brand — and what to change to improve it.
Buyers increasingly research products by asking ChatGPT, Claude, Gemini, and Perplexity instead of searching Google. Those answers name a handful of brands and cite a handful of sources. Myrah measures whether a brand is among them.
Myrah builds the set of questions buyers actually ask in a category — comparison, use case, and category queries, with branded prompts excluded so scores aren't inflated by questions a brand wins by default. It runs those questions across supported AI models on a schedule, capturing the full answer, every brand named, the order they appear in, and every source cited.
From each run, teams get:
• Visibility and share of voice against named competitors, broken out by model and by question
• Sentiment and positioning — how AI characterizes the brand, not only whether it appears
• Citation and source tracking — the specific pages models pull from when deciding who to recommend
• A prioritized gap list — the exact questions the brand is missing, with the underlying answer attached as evidence
• Drafts from the Fix Agent — it writes the page or section that closes a gap, with headings, schema, FAQ, and internal links, exportable as clean Markdown or HTML for any CMS
• Scheduled re-runs and run history, so published changes can be traced to movement in the score
Agencies and multi-brand teams can run the same methodology across several brands in one workspace, with white-label client reporting.
Myrah is built for marketing teams, agencies, and founders who need AI search treated as a measurable channel rather than a screenshot.
