TL;DR

CitedSpy is a purpose-built Generative Engine Optimization (GEO) platform that tracks how AI assistants (ChatGPT, Perplexity, Gemini, Copilot, Claude, Google AI Mode and Grok) describe and recommend your brand. It collects live UI answers (not only API responses), aggregates repeated observations across engines and locales, and turns those signals into a visibility score, competitor share-of-voice, citation-source database and prioritized action items. For agencies, consultants and founders who need to know not just whether AI mentions them but why and what to fix, CitedSpy provides a clear measurement-to-action workflow.

What it is and who it’s for

CitedSpy targets agencies, SEO consultants, marketing teams, ecommerce brands and bootstrapped startups that want a practical way to understand and improve their presence inside AI-generated answers. It’s especially useful when teams can’t justify large enterprise contracts but still need reliable GEO insights and client-ready reporting.

Core strengths (features-first)

Multi-engine, live-interface tracking

Runs the same prompts across multiple AI assistants and captures answers from the live product interface rather than relying solely on APIs. That matters because API outputs and the UI that buyers see can diverge.
Prompts are executed repeatedly (several runs per week) so you get a mention rate and trend rather than a single snapshot. You can also set region/locale per prompt.

Share of voice and competitor benchmarking

Add multiple competitors and view mention rate, average position, sentiment and head-to-head win rates (how often an engine recommends you over a rival).
Share-of-voice charts and grouped mention-trend lines let you detect when a competitor gains ground.

Citation source tracking

Extracts and catalogs the domains AI assistants cite when recommending brands, producing a searchable database of the sources driving recommendations in your category.
Flags citation sources competitors use that you don’t, providing immediate areas to pursue (e.g., Reddit threads, Wikipedia paragraphs).

Action items and prioritization

Converts gaps into prioritized, actionable tasks with estimated impact and time to implement — the practical bridge between measurement and work.
Tasks range from content and schema fixes to outreach opportunities tied to specific domains or threads.

Prompt research + AI Content Studio

Suggests relevant queries to track (avoids redundant near-duplicates), which improves the signal quality.
Content Studio generates briefs, outlines and drafts grounded in the actual citation and competitor data CitedSpy has observed, shortening the path from insight to published content.

Agency and integration tooling

Workspaces, role-based access, white-labeling, custom domains and PDF reporting for agency clients.
Integrations: Zapier, Looker Studio connector, Slack, WordPress, Shopify, Salla, webhooks and an MCP server linking analytics into Claude/GPT workflows.
API access for teams that want to export or embed data elsewhere.

What works well in practice

The live-answer approach and repeated sampling produce defensible, repeatable metrics (share of voice, mention rate, sentiment) that teams can report on and act upon.
Citation database and the "why" behind visibility problems are high-value: knowing which sources drive AI recommendations is often the fastest path to improvement.
The end-to-end workflow (discover prompt gaps → surface sources → create prioritized tasks → generate content) is built for execution and agency deliverables.

Limitations and areas to watch

Dashboard UI and parsed outputs are primarily English today; multilingual prompt handling and fully localized UI are on the roadmap but not yet complete. Responses are parsed into English by the platform, which can be limiting for non-English-first teams.
Some content-generation capabilities (article generation and optimization) currently live in the dashboard and are not yet fully available inside the MCP or public API — though roadmap items suggest expansion here.
Transparency and historical tracking could be deeper — some users asked for clearer attribution of which exact prompt run, model, time and source contributed to a metric. Improved traceability would strengthen audits.
Credit usage: prompts consume answer credits per engine, which is worth understanding when designing tracking cadence.

Suggested improvements

Faster rollout of multilingual parsing and UI localization so non-English markets can use full functionality without workaround.
Deeper integrations with traffic/behavioral sources (e.g., direct Google Search Console integration) to correlate AI visibility with site performance.
More granular historical playback and traceability: show the exact run/model/source that produced each mention to simplify audits and client proofs.

Verdict

CitedSpy is a focused, execution-oriented GEO tool that shifts the conversation from “Are we visible to AI?” to “Why are we visible (or not), and what exact work will change that?” Its live-interface sampling, citation database and prioritized action items make it particularly valuable for agencies and growth teams that must convert insights into billable, measurable work. If your priority is understanding and improving brand presence inside AI assistants — not just measuring it — CitedSpy delivers a pragmatic, well-integrated workflow with sensible agency features. Consider it especially if you need multi-engine coverage and want a platform that couples measurement with a clear operations playbook.