PodcastBanklessSal Ternullo

NEAR Just Got Its First ETF. What Happens Next?

NEAR Intents has expanded into swaps involving tokenized equities, while reported early inflows and trading activity put the Bitwise NEAR ETF launch in focus. The discussion also highlights Intents' transaction volume and buyback mechanism, alongside an argument that NEAR's valuation could compare favorably with AI platforms that have traction. Separately, speakers discuss privacy-focused AI infrastructure and the view that NEAR's investment case is closely tied to AI.

AltcoinsCrypto MarketsArtificial Intelligence

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Key Takeaways

NEAR Intents has expanded from digital-asset swaps to swaps involving tokenized equities, including 400 products introduced with Ono, and has processed more than $32 billion in volume. As transaction take rates scale, net revenue funds buybacks of NEAR held in a permanent capital vehicle; the tokens are not currently burned, though the community could choose to burn them later.

One speaker describes a tiered enterprise AI setup that uses frontier models for non-confidential tasks, open-source models in confidential-computing environments, and a router for policy and control. Another speaker predicts that unshared services will need privacy-guaranteeing architecture two years out, while citing Google search trends as a rough proxy showing privacy interest at a peak multiple times higher than any other in the past 30 years.

The Bitwise NEAR ETF reportedly attracted about $50 million in its first three days, with its representative citing more than $10 million in daily inflows and $10 million to $20 million in daily trading volume. A speaker said an ETF can launch successfully in a bear market, while noting that Bitcoin remained meaningfully below its all-time highs even as sentiment was turning.

TECHNOLOGY

Intents Expansion — NEAR Intents lets users specify an outcome for solvers to fulfill. It has expanded from digital-asset swaps to swaps between digital assets and tokenized equities, including 400 tokenized equity products introduced with Ono.

“so intense David I think we talked about this when we were on last time but the intense framework is really the idea of a user expressing the outcome that…”—

Enterprise AI — One speaker describes a tiered enterprise AI architecture: frontier models handle tasks without highly confidential information, while open-source models run in confidential-computing environments. A router layer enforces policy and manages control.

“but certainly within the enterprise market, you're seeing the emergence of kind of these tiered structures that are leveraging frontier intelligence for tasks that are not, you know, highly confidential…”—

MARKETS

NEAR ETF Launch — The Bitwise NEAR ETF reportedly drew about $50 million in inflows during its first three days. Separately, the ETF's representative said inflows exceeded $10 million a day and trading volume ranged from $10 million to $20 million a day, calling the launch strong relative to other single-crypto-asset ETF launches that year.

“And you know, and it's not true of every asset. So, in the in the first three days, I think something like 50 million of inflows into NR…”—

Intents Buybacks — NEAR Intents has processed more than $32 billion in volume and is beginning to scale transaction take rates. Net revenue funds buybacks of NEAR tokens held in a permanent capital vehicle; the tokens are not currently burned, though the community could decide to burn them later.

“Behind those human interactions we process more than 32 billion in volume on the system and are starting to scale the take rates in each of those transactions in a…”—

ETF Staking — The Bitwise NRR ETF handles staking for investors, so they do not have to manage that step themselves.

“I mean the first of course and simple is that the ETF handles staking on behalf of investors…”—

FORECASTS

AI And NEAR — One speaker argues that an AI bull market would, in some ways, also be a NEAR bull market. The speaker says removing AI would make the NEAR thesis far less compelling.

“The cool thing about Near is that it is one part in crypto but is one part built for AI…”—

NEAR’s New ETF

The hosts introduce Bitwise’s new NEAR ETF and revisit an earlier claim that NEAR was undervalued, while the guest describes rising ecosystem activity and the need to build on that momentum.

Bitwise and NEAR

Hunter outlines Bitwise’s long involvement with NEAR, including research, a European ETP, staking, and work on Intents; the speakers emphasize that the ETF follows years of ecosystem engagement.

Selling NEAR to Investors

Hunter says investors need not master crypto rankings to understand NEAR: its connection to AI offers a clear entry point, while portfolio fit depends on each investor’s goals.

Intents and Buybacks

The guest explains that NEAR Intents routes user requests through solvers, now supports swaps with tokenized equities, and has processed substantial volume that generates revenue for NEAR buybacks.

Staking and ETF Demand

The speakers clarify that buyback tokens are held rather than burned, discuss possible future supply and incentive choices, and describe the ETF’s staking feature and early demand.

The AI Opportunity

Hunter cites strong early ETF inflows and trading, while both guests argue that NEAR may look inexpensive beside AI platforms with traction and that its outlook is closely tied to AI.

Many Models, Many Chains

The guests expect a fragmented future of many AI models, agents, blockchains, and stablecoins, arguing that NEAR can simplify movement across those systems and that execution and team quality matter.

AI Privacy

The speakers discuss private AI inference, enterprise privacy needs, and evidence of rising consumer interest, framing confidential AI infrastructure as an increasingly important requirement.

Closing Thoughts

The hosts and guests close by welcoming the ETF and connecting NEAR’s crypto and AI focus to a rapidly changing technology landscape before the standard risk disclaimer.

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Important Disclaimers

Not Investment Advice: For education only — not financial, tax or legal advice.

AI-Generated: Made by AI from source transcripts and may contain errors.

No Guarantees: Past performance does not predict future results; investing carries risk.

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