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Track and optimize your brand recommendations across AI search.
- Audits AI model responses across multiple generative engines to track brand mention frequency and recommendation share. - Pinpoints specific buyer-intent prompt matrices where competitors are cited instead of your product. - Identifies the underlying structural or contextual reasons causing your brand to miss out on AI citations. - Delivers actionable content and visibility reports tailored for product marketing, growth, and demand-gen teams.
Tracks emerging zero-trust buyer behaviors where enterprise customers rely on AI recommendations rather than traditional search engines. Provides precise prompt-level visibility data to replace generic keyword tracking with actionable AI citation metrics. Helps software brands capture high-intent traffic by aligning digital footprints with how LLMs source information. Automates the continuous auditing process across multiple competing generative models to save manual research time.
Category: AI & Automation
Team Size: 2-10
Visit WebsiteCited is an AI recommendation intelligence and search visibility platform built for B2B and B2B2C software businesses. It continuously monitors how generative AI engines like ChatGPT, Claude, and Gemini recommend brands compared to competitors when buyers ask for category leaders. The platform analyzes visibility gaps, uncovers why competitors are cited instead, and generates actionable content optimizations to improve share of AI voice.
Cited was founded by Parth Sesodia and a team of B2B marketers based in Pune, India, operating under Upfolio Labs. Recognizing that buyers had largely replaced multi-tab web research with direct conversations with LLMs, the creators built Cited to help software brands track, measure, and influence how AI models discover and recommend their products.