AI engines describe your brand every day. Hear what they say.
Citationly monitors how ChatGPT, Gemini, Claude, Perplexity, Copilot, and Grok describe your company, products, and pricing, then flags every inaccuracy before it reaches another buyer.
Your brand story is being retold without you in the room
Every time someone asks an AI engine about your company, the engine composes a description of what you do, what you cost, how you compare, and whether you can be trusted. That description draws from whatever sources the engine found, weighted however its model decided. Sometimes it is accurate. Sometimes it is outdated pricing, a discontinued product, a competitor's claim repeated as fact, or a misreading of your positioning.
Traditional brand monitoring watches news, social media, and review sites, but none of it sees inside AI answers, which is where a growing share of first impressions now forms. A prospect who receives a wrong answer about your product does not email you to check. They simply move on, and you never learn the conversation happened.
For enterprises, the exposure scales with volume. One flawed source can shape thousands of answers a day, quietly, across every engine that ingested it. The longer misinformation circulates undetected, the more deeply it settles into the answers buyers receive.
AI brand monitoring that catches problems at answer level
Citationly continuously asks the questions buyers ask about your brand, across all six engines, and analyzes every answer that comes back. Each mention is recorded with its context: how the engine described you, what claims it made, what sources it leaned on, and whether the description matches reality.
When something is wrong, you know quickly. Incorrect pricing, misattributed features, outdated leadership details, or a stale competitor comparison all surface as flagged mentions, with the answer text and likely source attached. Your team sees not just that an engine is wrong, but why, which is what makes correction possible.
The value compounds beyond defense. Monitoring reveals how engines position you when they get it right: which strengths they emphasize, which use cases they associate with you, and how your described identity compares to the one your marketing intends. That gap between intended and machine-perceived positioning feeds directly into your broader AI visibility picture, and it is strategy-grade insight most brands have never seen.
Six ways Citationly watches over your brand.
Continuous Mention Capture
Every brand, product, and executive mention across six engines, recorded with full answer context. Nothing engines say about you goes unobserved, closing the blind spot traditional monitoring leaves open.
Accuracy Flagging
Detection of answers that misstate your pricing, features, availability, or positioning against your verified brand facts. Misinformation gets caught in days, not discovered months later through a confused sales call.
Sentiment and Framing Analysis
Classification of how each mention frames your brand: recommended, neutral, cautionary, or negative. Distinguishes healthy visibility from harmful visibility, so effort goes where the risk is.
Source Tracing
Identification of the likely source content behind inaccurate or negative answers, connected to citation data. Correction happens at the root, because fixing the source fixes the thousands of answers built on it.
Product and Executive Coverage
Monitoring extends beyond the company name to product lines, brand variants, and named leadership. Protects the full brand surface, since buyers ask engines about products and people, not just companies.
Alerting and Escalation
Configurable alerts when new inaccuracies appear, sentiment shifts, or mention volume spikes unusually. Brand and communications teams respond on their timeline, not after the damage has circulated.
From verified facts to corrected answers.
Five steps, from establishing a baseline to verifying a correction actually worked.
Your brand facts get established
Products, pricing, positioning, and key details are recorded as the verified reference.
Engines are questioned continuously
Citationly asks the brand questions buyers actually ask, across all six engines.
Every mention is analyzed
Answers are checked against your verified facts and classified for accuracy and framing.
Problems surface with evidence
Flagged mentions arrive with answer text, engine, and likely source, ready for action.
Corrections get verified
After your team updates the source content, subsequent scans confirm whether engine answers actually changed.
What changes when brand monitoring goes proactive.
Reputation risk shrinks
AI reputation management becomes proactive. Problems are found by your dashboard, not your prospects.
Sales conversations improve
Teams enter deals knowing what engines told the buyer first, ready to reinforce or correct it.
Positioning gets sharper
The gap between how you describe yourself and how engines describe you becomes visible and closable.
Legal and compliance exposure drops
In regulated industries, documented monitoring of machine-generated claims is fast becoming an expectation.
Trust in the channel grows
Once leadership sees AI answers being managed like any other brand surface, investment follows naturally.
Brand monitoring built for the answer, not just the mention.
Answer-level depth
Many tools count mentions. Citationly reads them, checks them against your verified facts, and explains what is wrong and where it came from.
Connected to the fix
Monitoring links directly to citation tracking and optimization workflows, so a flagged problem becomes an assigned correction, not a screenshot in a slide deck.
Full engine coverage
Six engines monitored with one methodology.
Built for accountability
Mention history, flags, and resolution status are recorded, giving brand teams the audit trail enterprise governance expects.
Find out what AI engines are telling your buyers
Run a free analysis and see how six AI engines currently describe your brand, with any inaccuracies flagged from the first scan.