DEEP DIVE
Evaluating the AI Visibility Tool Landscape
The measurement models that underpin SEO are no longer sufficient on their own. Generative Engine Optimisation (GEO) challenges us to rethink what visibility means and, more importantly, how to measure and quantify Large Language Models (LLM) and Artificial Intelligence (AI) search best practices.
In this study, we have investigated 26 different AI visibility tools during Q4 2025, aiming to find the best tools to help navigate in the GEO landscape and meet our criteria.
AI visibility tool assessment criteria
Measuring GEO and AI search requires an extensive measurement framework and solid plan for what to measure before evaluating which tools can provide the answers. LLM search visibility tools are still relatively new, and the tooling ecosystem reflects that. We assessed each tool against eight enterprise-grade criteria.
AI platform coverage
Depth of analytics
Global reach and multi-language support
Content gap analysis
API integrations
Data accuracy
Transparency of methodology
Enterprise and agency readiness
From this process, six tools were researched in depth:
Profound
Nimt
Promptwatch
Writesonic
Otterly
AI Waikay
After a deeper research of the six tools, three stood out.
The top three: Strategic Options
After extensive testing of the market, three GEO visibility tools best met the above criteria; Promptwatch, Writesonic and Profound.
Promptwatch (NL): Balanced Visibility and Compliance
Promptwatch offers broad feature coverage, strong data transparency, and a flexible structure that supports detailed analysis across clients, markets, and prompts. Being based in the Netherlands also means a strong understanding of EU regulatory requirements, an important factor for many organisations. Reasons why Promptwatch stood out:
Comprehensive monitoring across all major AI platforms
Reproducible, verifiable data
Clear and transparent metrics
Flexible setup for detailed, client-level analysis
Existing and evolving API integrations
Direct access to product developers
The multi-monitor structure allows tracking prompts, products, and markets separately while maintaining a central overview, making it easier to detect shifts, demonstrate value, and act quickly.
Writesonic (US): High-Volume Content Execution
Writesonic excels where analysis and execution need to live in the same workflow. In addition to GEO and SEO monitoring, it offers AI-driven content creation tools, enabling teams to turn insights directly into copy. It is best suited for high-volume content strategies and rapid experimentation which was not the primary focus in this study.
Profound (US): Advanced Analytics for Enterprises
Profound is built for depth, delivering sophisticated analytics across multiple AI engines, including share of voice, sentiment analysis, and conversation-level insights. It also provides demographic data and estimates of prompt volume. These figures should be treated as directional rather than exact, as they are based on anonymised modelled datasets rather than direct data from AI search platforms, which can introduce sampling bias, especially for niche audiences.
Profound is particularly well suited to large organisations that require detailed, LLM-specific reporting and strategic intelligence rather than content production capabilities.
A best practise for choosing AI search visibility tools
In summary, LLM-driven search is still an emerging field, and definitive best practices have yet to be established. However, it is clear that structured measurement matters. By defining what to measure, how to measure it, and which tools can be trusted, organisations can move closer to a search visibility measurement process. A solid AI search visibility tool framework enables teams to act on real insights, effectively benchmark, and adapt as models evolve. In a landscape where uncertainty is the only certainty, measurement becomes the anchor.
If you need help measuring and optimising your GEO visibility, we’d be happy to help you turn AI search into a competitive edge.