Bitwise and SVRN Bet on NEAR as AI Infrastructure Thesis Gains Traction

Asset management firm Bitwise has positioned the NEAR Protocol ($NEAR) as a focal point of its investment strategy, driven by the conviction that future digital asset performance will be dictated by specialized, utility-driven networks. Bitwise Chief Investment Officer Matt Hougan views $NEAR as a rare asset offering immediate real-world transactional capacity paired with long-term infrastructure tailored for the expanding artificial intelligence ecosystem.

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. While this perspective represents an active portfolio thesis rather than a guaranteed outcome, Hougan emphasized that long-term viability requires a committed community and practical demand: The thing that kills an ETF is if no one cares, he noted, adding that $NEAR’s core appeal lies in its operational cross-chain capabilities and ambitions to power AI-driven commerce.

Financial Advisers Drive Early Demand for Bitwise’s NRR

The launch of Bitwise’s $NEAR product, trading under the ticker NRR, is seeing capital inflows that diverge from traditional digital asset product launches. Rather than attracting only legacy holders or native crypto participants, Hougan noted that internal reports reflect earlier-than-expected interest from financial advisers. Although trading data limits full visibility into buyer identities, market appetite appears anchored to the structural convergence of two rapidly expanding sectors.

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

The NRR vehicle incorporates an automated staking design that directly benefits fund performance. The staking yield gets added back into the net asset value. It’s not distributed, Hougan explained. While token staking can complicate redemptions during volatile conditions, Hougan pointed to $NEAR’s relatively brief unstaking window, specialized extended settlement agreements for market makers, and dedicated liquidity mechanics designed to handle market stress.

SVRN Integrates Operational Infrastructure with a 10% Supply Target

Alongside passive fund exposure, corporate entity SVRN is pursuing a dual-track strategy led by Chief Executive Officer Ternullo. SVRN has established a long-term goal of accumulating 10% of the entire $NEAR token supply, effectively acquiring one out of every ten tokens in existence. However, the firm aims to combine balance-sheet accumulation with active, on-chain operational roles.

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

Beyond validator infrastructure, SVRN has expanded into systems supporting $NEAR Intents, confidential transactions, and cash-generating enterprises through its acquisition of Fastnear. The company is also emphasizing private AI inference—a critical technological priority designed to safeguard model inputs and outputs during execution. Ternullo outlined how enterprise capital deployment could evolve as the firm balances asset ownership against infrastructure investment:

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.

The Bridge Between AI Adoption and Token Value Accrual

The broader investment thesis for both Bitwise and SVRN rests on converting technical network throughput into tangible, sustainable token demand. Ternullo noted that $NEAR Intents has already processed over $34 billion in total transaction volume, though an estimated 98% of those transactions currently stem from human activity. The widespread execution of autonomous AI-agent commerce remains a future growth vector.

Ternullo maintain that economic throughput will directly feed the token’s valuation: 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, he said. And so as we prove the $NEAR AI revenue model and token buyback system, value accrual to $NEAR will only increase.

Why This Matters

The dual strategies represented by Bitwise’s NRR and SVRN highlight a maturing institutional framework for investing in layer-1 blockchains. While traditional funds like NRR package exposure and reinvested staking rewards to mitigate structural overhead, operating entities like SVRN combine asset ownership with operating businesses and validator risk. The success of both approaches will serve as a bellwether for whether networks bridging blockchain functionality and AI workloads can convert early developer adoption into measurable economic returns for token holders.

Frequently Asked Questions

How does the Bitwise NRR fund handle staking rewards?

Staking yields generated within the NRR fund are not paid out as regular cash distributions. Instead, the staking rewards are directly reinvested and added back into the fund’s net asset value (NAV), allowing the value of the holdings to compound within the fund.

What is SVRN’s strategic goal within the NEAR ecosystem?

SVRN has set a long-term target to acquire 10% of the entire circulating supply of $NEAR tokens. In parallel with asset accumulation, SVRN actively builds and operates ecosystem infrastructure, managing six white-labeled validators and developing services for private AI inference, network intents, and developer tools via Fastnear.

How much transaction volume has $NEAR Intents processed?

According to SVRN CEO Ternullo, $NEAR Intents has surpassed $34 billion in cumulative volume. Approximately 98% of that activity is currently generated by human users, with automated AI-agent transactions representing the network’s next targeted phase of expansion.