Testing the Top GEO Tools: AirOps, Profound, and Yolando Compared

The Internet No Longer Starts with Search

The customer journey rarely starts with a traditional search bar in 2025; it starts with a question to an AI assistant. Instead of showing ten blue links, these assistants generate a single, synthesized answer that determines who gets discovered or bought, and who quietly disappears. The new frontier of visibility isn't about ranking higher; it's about being read, trusted, and cited by machines that mediate every recommendation.

This is why a new class of tools, AirOps, Profound, and Yolando, step in.

Why Tools Like These Now Matter

As language models become the front door to online experiences, brands face three simultaneous pressures:

• Volume Pressure: Companies must produce high-quality, contextual content faster than ever.

• Visibility Pressure: They need to understand how and where AI systems reference them.

• Comprehension Pressure: Their data must be structured in a way AI can actually interpret and trust.

Traditional SEO and advertising stacks were never designed for this environment. Generative AI requires a hybrid model: creativity + visibility + structure. That’s the foundation AirOps, Profound, and Yolando each build upon, each addressing a different phase of AI discoverability maturity.

1. Yolando — The Discoverability Engine

Founded: 2025 | Core Function: AI Discoverability, Generative Engine Optimization (GEO), and Content Infrastructure

Yolando is the backbone of AI discoverability. It builds the structured intelligence layer that makes your brand’s content, product data, reviews, and messaging machine-readable, verifiable, and recommendable across platforms like ChatGPT, Gemini, and Perplexity.

In practice, Yolando transforms existing content into an organized knowledge base (RAG) that AI systems can easily understand and trust. It tracks how your brand appears in AI-generated answers, identifies who gets cited, and pinpoints where visibility can improve.

Where AirOps creates content and Profound measures its perception, Yolando ensures that AI can both find and trust your brand, closing the gap between what you publish and what AI platforms recommend.

Core Capabilities for GEO Readiness:

• Knowledge Layer (RAG Engine): Continuously builds a structured, AI-ready knowledge base from your website, internal assets, and public data. This gives LLMs clean, verified information to pull from, which dramatically improves how accurately they generate content about your brand and how confidently they recommend you.

• Insights Dashboard: Measures Discoverability, Share of Voice, Reputation Score, and Citation Share across AI platforms, showing who’s being recommended and why. You see exactly where you’re winning or losing in AI-generated answers, enabling smarter content decisions that directly boost your presence in recommendations.

• Citation Tracking: Reveals which sources AI models cite, your own, competitors’, or third-party, exposing who truly shapes the narrative. You can identify where to strengthen or correct your content so AI systems cite you instead of someone else, increasing your recommendation share.

• Prompt Intelligence: Runs branded and unbranded prompts daily to track AI visibility and uncover new opportunities. You discover the exact phrases, topics, and intents where you’re missing, allowing your team to generate the right content to influence recommendations.

• Action Engine: Converts insights into execution, generating optimized, on-brand content to close visibility gaps and earn citations. You instantly turn insights into content that improves how AI models perceive, describe, and recommend your brand—closing the loop between strategy and impact.

Together, these features form a closed-loop discoverability system that continually strengthens your AI visibility.

Strategic Position and Brand Integration:

In the emerging AI marketing stack, Yolando is the infrastructure layer between workflow orchestration (Airops) and measurement (Profound).

• For CMOs: A strategic visibility engine translating brand assets into structured data AI can parse and cite.

• For Content Teams: A unified workspace combining brand voice, competitor analysis, and AEO insights.

• For Executives: A single-source dashboard revealing how your brand ranks and reads in AI ecosystems.

Yolando bridges the gap between what your brand says and what AI says about your brand, turning narrative risk into measurable visibility.

Takeaway: AI visibility now depends on being readable, citable, and trusted by machines, not just searchable by humans. Yolando turns your brand’s content into structured, verifiable data, ensuring you show up in the answers, not just the queries.

2. AirOps — Workflow-Driven Content Scaling

Founded: 2022 | Core Function: Content Workflow Automation and AI-Powered Creation

AirOps is designed to scale content creation through customizable workflows that integrate large language models into editorial planning, content generation, and SEO workflows. It's a robust solution for operationalizing content production, addressing the Volume Pressure.

Strengths for Scalable Content Ops:

• Workflow-First Architecture: Enables teams to design no-code content workflows that integrate research, drafting, review, and publishing.

• Human-in-the-Loop: Ensures brand safety and tone through checkpoints and Brand Kits that control voice and editorial consistency.

• Platform Integration: Connects with WordPress, Webflow, Notion, and more, enabling end-to-end content orchestration.

Limitations for GEO and AI Visibility:

• Limited AI Optimization: While strong at creating content, it does not deeply focus on structured data for AI extraction.

• No Citation Tracking: AirOps lacks tools to measure how brands appear in AI assistant outputs.

• Partial Schema and RAG Support: Its ability to generate structured knowledge bases or verify brand presence across AI models is minima.

• Complex to Operationalize for GEO: Implementing AI-native visibility initiatives within AirOps can be challenging, requiring specialized knowledge, cross-team coordination, and ongoing experimentation to achieve measurable results.

Takeaway: AirOps is ideal for scaling high-volume content production in a controlled and efficient manner. However, implementing it for AI-native visibility can be complex, success depends on disciplined workflow design, cross-functional alignment, and a clear understanding of how AI interprets structured data. Brands looking to ensure AI models not only read but cite their data will need more advanced discoverability infrastructure and ongoing operational maturity.

3. Profound AI — Seeing How AI Sees You

Founded: 2024 | Core Function: AI Visibility Tracking & Answer Engine Analytics

Profound AI delivers essential situational awareness by tracking AI citations across LLMs such as ChatGPT, Gemini, or Perplexity. Instead of tracking traditional page rankings, it tracks the frequency and context in which a brand is mentioned, directly addressing the Visibility Pressure.

Strengths for AI Citation Monitoring:

• Tracks Brand Mentions Across LLMs: Updates visibility insights every 24 hours across leading closed-source models.

• Provides Benchmarking Data: Offers share-of-voice and competitor comparisons within AI-generated responses.

• Includes Sentiment Analysis: Determines how AI interprets your brand tone and positioning.

Limitations for Execution:

While Profound is great at measurement, it does not provide the tools necessary to fix the visibility issues it identifies.

• Diagnostic, Not Prescriptive: Profound identifies gaps but lacks mechanisms to resolve them.

• Lacks Structured Data Recommendations: Doesn’t guide content restructuring for improved AI readability.

• Needs Pairing with Execution Tools: Requires additional platforms like AirOps or Yolando for remediation.

Takeaway: Profound gives brands a window into how they’re perceived by AI, serving as the visibility radar necessary before optimizing discoverability.

Comparative Analysis

Choosing by Maturity Stage

Each of these platforms addresses a specific aspect of the evolving AI-discoverability process, but the most effective strategies often combine multiple layers, creation, measurement, and integration.

Yolando is adaptable across all stages, supporting early experimentation as well as mature GEO implementation.

Airops, Profound, and Yolando serve different but complementary purposes. Organizations may begin with creation and monitoring tools and later integrate discoverability systems to ensure that their content and data remain visible and interpretable across AI ecosystems.

Final Thoughts: From Keywords to Knowledge

Once, visibility meant ranking higher. Now, it means being recognized, by algorithms that summarize, recommend, and decide what humans see next.

AirOps ensures your story is delivered, standardizing and automating content pipelines.

Profound ensures it’s heard, revealing how AI models perceive and reference your brand.

Yolando ensures it’s understood and remembered, translating content into structured knowledge that machines can trust, cite, and amplify.

Together, they represent the new visibility stack for an algorithmic world. The brands that master all three layers, creation, monitoring, and machine readiness, will define the next decade of digital presence. Those that don’t will vanish into the whitespace between AI’s answers.

In an era where every customer journey begins with a conversation, not a query, being understood by machines isn’t just technical fluency, it's marketing literacy. The future doesn’t belong to the loudest voices, but to the clearest data.