150 SaaS Brands Ranked by AI Visibility

Our analysis reveals four critical insights that reshape how we understand brand visibility in the age of generative AI.

1. The Design Advantage

Design and creative tools dominate the top rankings, with Figma (80.3), Canva (78.8), and Miro (77.8) all scoring exceptionally well. This advantage stems from LLMs' comprehensive understanding of creative workflows, likely due to extensive design documentation and tutorials in their training data. These brands benefit from clear use cases and strong mental models that LLMs can articulate effectively to users seeking creative solutions.

2. The Security Trust Factor

Security and compliance tools consistently outperform their category averages. 1Password (79.6), Okta (76.9), and Auth0 (76.8) demonstrate that trust-based positioning translates effectively to AI recommendations. LLMs appear to have strong mental models around security concepts and readily recommend established players in this space, particularly when users express concerns about data protection or compliance requirements.

3. The AI-Native Paradox

Counterintuitively, AI-first companies struggle for recognition. Copy.ai (74.5) and Writer (74.4) score below the category average despite building products specifically for the AI era. This paradox suggests that being "AI-native" doesn't automatically translate to AI visibility. Traditional brands with strong category positioning often outperform newer AI-focused alternatives, highlighting the importance of established mental models over recency.

4. The Giant's Struggle

Enterprise giants face unexpected challenges. Salesforce (77.3) and HubSpot (77.5) rank lower than focused competitors, suggesting that breadth can dilute AI perception. When LLMs evaluate software recommendations, they often favor tools with clear, specific use cases over broad platforms. This trend favors specialized solutions and challenges the assumption that market leadership guarantees AI visibility.

5. The Density Problem

The middle tier (ranks 20-100) shows remarkable score compression, with 60% of brands clustering between 74-78 points. This density creates both opportunity and vulnerability – small improvements in AI perception can drive significant ranking changes, while neglecting GEO optimization can quickly erode position. Brands in this tier must focus on differentiation and clarity to break through the competitive middle ground.

Based on our analysis of 150 brands across 15,000+ AI interactions, here are actionable strategies for improving your brand's AI visibility and accuracy.

Priority Framework

If you're in the bottom 50 (ranks 100-150): Focus on basic accuracy first. Ensure AI models have correct fundamental information about your product, pricing, and core features. Visibility can wait until accuracy improves.

If you're in the middle tier (ranks 25-100): Balance accuracy improvements with selective visibility initiatives. Target specific use cases where you can clearly differentiate from competitors.

If you're in the top 25: Maintain accuracy while expanding recommendation strength. Focus on becoming the default suggestion for your primary use cases across all LLMs.

Content Strategy

Create content that directly addresses the queries LLMs receive about your category. Our analysis shows that brands with comprehensive FAQ sections, detailed feature comparisons, and clear use case documentation score significantly higher across all dimensions.

Avoid generic marketing speak in favor of specific, technical accuracy. LLMs respond better to precise feature descriptions than promotional language, and users increasingly trust AI responses that provide concrete, actionable information.