Sal Ternullo

$20 billion of volume that's been processed to date on Intense, and we now have billions of agents interacting, and this is one of the top platforms to interact on.

You can see a world where even just Intense volume starts to scale towards the point that we described in a research piece we published back in, I believe, March 2020.

that looks at $175 million effectively of daily volume through Intents at the current take rates, being the point at which the buyback pressure through just Intents exceeds the total issuance from the protocol over time.

That doesn't even contemplate mechanic design around IronClaw and NearAI, which are also looking at similar types of value accrual mechanics to NearToken.

And so I think when you're contemplating like, how do I underwrite this and think about a 20x or 50x opportunity?

It's extrapolating from the fundamentals that we already see live right now, you can check yourself to what does the future look like and where is near positioned in context of competitors to capture these agentic interactions at scale.

And obviously, given my role and job, I view that as they are the leader in that category and the opportunity is huge.

Yeah, it's a really good question.

There's an analogy to kind of the public cloud adoption era that I like to use as I'm describing this.

If you go back, AWS 2008, 2009, we started to see the emergence of cloud service providers

I was working at the time at State Street and the mid-2010s regulated tier one financial institution, systemically important bank, you know, all sorts of regulatory guardrails and overhead.

And in the early days, even in 2014-15, there was a massive hesitation to embrace public cloud and shared infrastructure, specifically because of data compliance requirements and data security issues.

confidentiality and intellectual property.

There are all sorts of concerns that prevented highly regulated institutions from actually adopting cloud infrastructure.

Fast forward to where we are today in 2026, cloud infrastructure is by far the predominant infrastructure platform for all regulated institutions.

And it's

The reason that we got here is because ultimately the controls that focused on security and compliance and data management got to a place inside these cloud environments where you actually have a greater degree of assurance over issues related to compromise or exfiltration of data than you would if you were running private data center footprints yourself.

And so we're in that similar adoption curve now on the AI side where

I believe that we will ultimately end up with shared services infrastructure that allows for these same attributes of security and privacy and confidentiality to be expressed to users and businesses who are using LLMs today.

If you look at the enterprise market, a common pattern for organizations that can't get comfortable with anthropic or open AI is to actually roll their own infrastructure inside their own AWS environment and deploy open source models that they control.