Bitwise, SVRN Bet on NEAR as AI Infrastructure Thesis Takes Shape

For Hougan, Bitwise’s chief investment officer, $NEAR offers exposure to a project whose existing transaction capabilities support a much larger ambition in AI. He believes investors will increasingly distinguish between cryptocurrencies based on what their networks deliver.

“Increasingly in the future, I think we’re going to see idiosyncratic returns specific to individual projects, how they execute and what market they’re going after,” Hougan said.

That is a portfolio thesis, rather than an established outcome. Its appeal depends on $NEAR developing sources of demand that distinguish it from the broader market. Hougan’s selection criteria also include staying power and a community with conviction.

“The thing that kills an ETF is if no one cares,” he said, adding that $NEAR’s appeal spans its existing cross-chain transaction capabilities and its ambition to support AI-driven commerce.

Financial Advisers Are Showing Up Early

NRR’s launch has attracted interest beyond the familiar buyers Hougan typically expects first: people who already follow or hold the underlying asset.

He said early internal reports indicate earlier-than-expected allocations from financial advisers. Those observations are anecdotal, as ETF trading does not give an issuer a complete picture of its buyers.

Hougan sees an explanation in the demand for investments connecting two powerful technology themes.

“I think the reason for that is the intersection of crypto and AI is just too attractive for anyone to ignore,” he said. “They’ve been hearing about that for the last two years, and now they have a way to express it.”

The fund also incorporates staking rewards. “The staking yield gets added back into the net asset value. It’s not distributed,” Hougan said.

Investors receive that benefit within the fund’s value, rather than through cash payouts. Redemptions introduce a separate challenge when tokens are staked, with Hougan pointing to $NEAR’s relatively short unstaking period, extended settlement arrangements for market makers and additional liquidity capabilities for extreme conditions.

SVRN’s Ambition Extends Beyond Its Treasury

SVRN’s stated long-term goal is to accumulate 10% of $NEAR’s token supply, a position equivalent to one in every 10 tokens. But Ternullo, its CEO, described a business intended to earn its place within the network as well as hold its asset.

“What this meant in the first chapter was building out the infrastructure that powers the network,” he said. “And so on our side, we now run six white-labeled validators.”

Ternullo also highlighted infrastructure supporting $NEAR Intents and confidential transactions, alongside the acquisition of Fastnear, which he described as a cash-generating infrastructure business.

Private AI inference, which protects prompts and outputs while models run, is another commercial priority. The ownership ambition could eventually require consideration of concentration and alternative uses of capital.

“There are a number of productive ways to put additional capital to work in the ecosystem, whether that’s further financing the infrastructure layer, supporting proprietary development of applications, and then commercializing those,” Ternullo said. “This would drive an evolution in how we allocate capital in the future.”

Where the AI Thesis Meets Investor Returns

Ternullo said $NEAR Intents had processed more than $34 billion in volume, with roughly 98% of interactions still human-driven. AI-agent commerce remains largely an opportunity ahead.

The investment question is whether that activity produces economic value for token holders.

“There is one asset; it is $NEAR. All value that’s generated in this ecosystem accrues to it, and that will always be the case,” Ternullo said. “And so as we prove the $NEAR AI revenue model and token buyback system, value accrual to $NEAR will only increase.”

That is the thesis investors must test. $NEAR’s transaction volume needs to translate into sustainable revenue and token demand.

For investors, the distinction is clear: NRR packages exposure and staking within a fund, while SVRN adds operating businesses and corporate execution risk. In the end, both ultimately depend on $NEAR turning adoption into economic value.