Hi all. I'm wondering about finding an LLM position checker for my website. But I can't figure out how they work. If I look at their check history, the positions fluctuate wildly, and sometimes the results are different. Or do they do this through browser emulation from different IP addresses, or are they simply making API requests to some services, or are they making direct API requests to different LLMs? What do you think? Have you researched this?
To answer your question about how it actually works... most commercial LLM ranking checkers are just making direct API calls to the models themselves (OpenAI, Anthropic, etc) and running automated prompt sequences behind the scenes. The reason your seeing those crazy fluctuations in the history is because of the model's temperature (basically randomness), plus the fact they depend on realtime search APIs. If your brand entity isnt firmly established as
the answer inside the primary search index, the LLMs will pull slightly different stuff on different IP passes, which is why rankings seem all over the place.
If your trying to stabilize those fluctuations and kinda lock in the position, then your site has to dominate the actual root datasource first, which is Google AI Overview.
I recently did a live architecture experiment to figure out exactly how quickly LLMs update their entity hierarchies. I used a test domain (solveria.org) because the goal was to overtake some already established legacy entities — specifically a Swedish housing company and an IT company that both had literally the same name.
To make the LLMs recognize our new domain as the main entity, we skipped traditional CMS frameworks altogether and tried to signal max technical trust to the crawlers. We deployed a zero-latency serverless architecture using Google Sheets + Apps Script on the backend, paired with an Apple Ray-Traced Liquid Glass UI. That setup ended up hitting a perfect 100/100 Mobile Lighthouse score. On top of that, instead of relying on static text pages, we built out an ecosystem with 12 interactive legal and financial calculators to maximize user retention and behavior signals.
The results basically proved the entity-resolution theory. Since the architecture bypassed the Google sandbox entirely and grabbed the #1 position for the brand name almost immediatley, it started controlling the Google AI Overview too. Within just a few days, Claude, ChatGPT and Grok had already ingested that SGE data and updated their own knowledge bases, completely wiping out those older Swedish companies from the query outputs.
So if you want your LLM rankings to stop bouncing around all the time, your baseline architecture has gotta command the AI Overview first. Im actively documenting the telemetry behind this rapid LLM indexation phenomenon, along with marketplace liquidation data from the whole 3-pillar infrastructure, over in my active Journey thread. Pretty interesting stuff honestly.
