I’ve recently been paying more attention to a product by DeAgentAI: the AI Token Smart Router. Many people are still asking, what exactly is the AI Token Smart Router?
In simple terms, it’s not building yet another new large language model. Instead, it consolidates the different AI models that enterprises previously had to integrate and call separately into a single unified entry point.
Previously, companies had to connect to multiple models, which often meant working with different vendors. Now, the Router is more like an “AI model master router”—it unifies multi-model calls so that enterprises can choose, measure, and reconcile more easily. Even more importantly, this product has moved beyond just a slide-deck stage.
According to data recently disclosed by the official team, during the trial operation phase, the AI Token Smart Router already had B2B customers using it. The latest official disclosures also show that since the start of its internal testing, it has served 8 B2B customers, processed more than 54 million external model calls in total, and monthly revenue has already exceeded $1 million. The product has now also been officially opened to B2B customers.
So I think what’s truly worth watching now is:
How many do these businesses actually use?
Can the Router keep generating revenue?
And how does that revenue ultimately connect back to $AIA?
That’s also what I find particularly interesting about the relationship between AI Token Smart Router and $AIA.
It’s currently following a fairly direct value chain: enterprises call AI → the Router generates commercial revenue → protocol/business revenue is generated → part of the funds is used for $AIA buybacks and burns.
DeAgentAI has also previously announced a mechanism for $AIA buyback and burn based on real protocol revenues.
So if, going forward, the number of the Router’s B2B customers, the volume of model calls, and revenue can continue to grow, then it’s effectively turning “AI usage volume” into “real business revenue,” which in turn creates value inflow back into $AIA.
Personally, I’m keeping a close eye on three data points:
① Whether the number of B2B customers continues to increase
② Whether the volume of model calls can keep rising beyond the tens-of-millions range
③ Whether the revenue → buyback/burn of $AIA link can continue to be realized
This is easier to verify than just telling the narrative of an AI project.
In plain words, what the AI Token Smart Router really needs to prove is one sentence: whether there are real enterprises using it, and whether these real calls can ultimately translate into real revenue.
In simple terms, it’s not building yet another new large language model. Instead, it consolidates the different AI models that enterprises previously had to integrate and call separately into a single unified entry point.
Previously, companies had to connect to multiple models, which often meant working with different vendors. Now, the Router is more like an “AI model master router”—it unifies multi-model calls so that enterprises can choose, measure, and reconcile more easily. Even more importantly, this product has moved beyond just a slide-deck stage.
According to data recently disclosed by the official team, during the trial operation phase, the AI Token Smart Router already had B2B customers using it. The latest official disclosures also show that since the start of its internal testing, it has served 8 B2B customers, processed more than 54 million external model calls in total, and monthly revenue has already exceeded $1 million. The product has now also been officially opened to B2B customers.
So I think what’s truly worth watching now is:
How many do these businesses actually use?
Can the Router keep generating revenue?
And how does that revenue ultimately connect back to $AIA?
That’s also what I find particularly interesting about the relationship between AI Token Smart Router and $AIA.
It’s currently following a fairly direct value chain: enterprises call AI → the Router generates commercial revenue → protocol/business revenue is generated → part of the funds is used for $AIA buybacks and burns.
DeAgentAI has also previously announced a mechanism for $AIA buyback and burn based on real protocol revenues.
So if, going forward, the number of the Router’s B2B customers, the volume of model calls, and revenue can continue to grow, then it’s effectively turning “AI usage volume” into “real business revenue,” which in turn creates value inflow back into $AIA.
Personally, I’m keeping a close eye on three data points:
① Whether the number of B2B customers continues to increase
② Whether the volume of model calls can keep rising beyond the tens-of-millions range
③ Whether the revenue → buyback/burn of $AIA link can continue to be realized
This is easier to verify than just telling the narrative of an AI project.
In plain words, what the AI Token Smart Router really needs to prove is one sentence: whether there are real enterprises using it, and whether these real calls can ultimately translate into real revenue.