Scrunch AXP via CDN: The New Reality for GEO and Mid-Market Scalability
If you have spent more than a decade in SEO, you’ve spent the last year watching your clients panic. First, it was the "death of the blue link," then it was the "AI Overviews are stealing my traffic" phase. Now, we’re pivoting to Generative Engine Optimization (GEO). But here is the problem: most agencies are treating GEO like it’s just another keyword ranking game. It isn’t.
If you are still providing monthly reports that track "top 10 positions" on Google, you are losing. The future isn't about rank; it’s about *answerability*. And the technical backbone of that shift? It’s the cdn geo implementation strategies that move content closer to the LLMs consuming it.
As an agency operator, I’ve stopped caring about "rank" and started caring about "access." If your content isn't being retrieved by ChatGPT or Perplexity because your site architecture is bloated and slow, your client is invisible. This is where the agent experience platform (AXP) comes in, and specifically, the concept of "scrunching" your data via a CDN for faster, cleaner ingestion.
GEO vs. Traditional SEO: The Metrics That Actually Matter
In traditional SEO, we obsessed over SERP features—featured snippets, sitelinks, and local packs. In GEO, we are optimizing for retrieval augmented generation (RAG). The LLM doesn’t "see" your CSS or your fancy hero animations. It sees the structured data, the semantic chunks, and the latency-optimized text packets served via your CDN.
I’ve spent the last six months stress-testing the major players in the space. My team keeps a live spreadsheet—yes, it’s a living document—tracking the pricing gotchas of every tool we trial. Why? Because I don't care about the shiny demo; I care about what happens when I onboard 10 more clients to a tool that charges per-seat or hides their API exports behind an "Enterprise" paywall.
Metric Traditional SEO GEO (Agent Experience) Primary Goal Click-through Rate Answer Citation/Source Credibility Target Audience Human Searcher LLM Context Window Technical Focus Core Web Vitals JSON-LD, Semantic Chunking, API Latency Data Source Search Console/GA4 LLM Prompt Logs & Citation Tracking
The Technical Shift: Why Scrunching Matters
When I talk about "scrunching" your AXP via a CDN, I’m talking about data optimization for machines. LLMs don't want a 2MB homepage loaded with tracking scripts. They want clean, cached, low-latency chunks of information. If you can serve your brand’s knowledge base via a CDN as a structured data stream (the core of an agent experience platform), you become the "source of truth" for the model.
This is where tools like Peec AI, Otterly.AI, and AthenaHQ come into play. They are trying to bridge the gap between "we have a website" and "we are a primary source for an AI agent."
The Tooling Audit: Peec AI, Otterly.AI, and AthenaHQ
I’ve tested these platforms with one question in mind: Does this scale?
Peec AI: Offers some interesting visibility metrics. However, I’m wary of any platform that promises "AI visibility" without transparently showing how they map to specific engine retrievals. If you use them, demand to see the raw data exports—if you can’t pull the data into a custom dashboard, you’re just renting a view, not owning your strategy. Otterly.AI: Strong focus on the content-to-agent pipeline. They understand that GEO is about the technical geo changes needed for modern RAG pipelines. But keep an eye on their pricing structure; if they start locking "advanced reporting" behind enterprise tiers, you’ll have to calculate if the client margins justify the cost. AthenaHQ: Useful for the operations side of content creation. It’s effective for managing the prompt-heavy side of the business, but always ask: "What breaks when we add 10 more clients?" If the system requires manual tagging per client, it isn't an agency tool—it's an agency bottleneck.
The Scalability Trap: Pricing and Agency Overhead
Here is where I get frustrated. Every new AI vendor arrives with a pitch that sounds like "we revolutionize your agency revenue." But then I look at their pricing page, and it’s a minefield of per-seat fees and "starting at" pricing that hides the real cost of scaling. As an agency lead, I refuse to work with platforms that punish growth.
If you are implementing an AXP for your clients, ensure the platform allows for:
Multi-tenant access: I don’t want to log in and out of 20 accounts. Give me a unified view. API Exportability: If your tool doesn’t play nice with BigQuery or Looker Studio, it stays in the "do not touch" pile. Model-Agnostic Tracking: Don't just show me how I rank in ChatGPT. Show me Perplexity, Claude, and Gemini. If a tool claims "comprehensive visibility" but only checks Google’s AI Overview, they are lying.
Actions and Recommendations vs. Raw Monitoring
Monitoring is a commodity. Every client can log into a dashboard and see numbers. Your value as an agency is in the actions. A raw monitoring report that says "Your visibility in Perplexity dropped by 5%" is useless noise.

Instead, your workflow should look like this:
Step 1: Technical Audit. Use your AXP to identify "chunking" failures. Is your content being fragmented by poor CDN delivery? Are your JSON-LD schemas actually being parsed by the LLMs?
Step 2: Semantic Gap Analysis. Use tools to see where the LLMs are hallucinating or citing competitors instead of you. If they aren't citing you, your "scrunching" isn't efficient enough.
Step 3: Implementation. Adjust the CDN cache rules. Optimize the text delivery for maximum semantic density.
Step 4: Report on Influence, not Rank. Move away from "rankings." Start reporting on "Citations within AI answers." If a client is being cited by Perplexity 40 times a month, that is a KPI you can actually sell to a C-suite executive.
Final Thoughts for the Agency Operator
GEO is not a phase. It is the evolution of information retrieval. If you are waiting for Google to "fix" their AI Overviews, you’re missing the boat. The win is in controlling how your clients’ data is consumed by every major model, not just the search giant.

My advice? Test everything. Demand raw data. Run away from pricing models that don't scale. And for heaven's sake, stop reporting on "blue links" unless you're prepared to explain why they don't matter anymore. If you keep building on the old metrics, you’re just building a sandcastle before the tide comes in.
Need a hand evaluating your current GEO stack? Check the spreadsheet toolify.ai against your current vendor list. If they can’t provide a clean CSV of your AI citation history, it’s time to move on.