NEAR Protocol keeps turning up in the conversations that matter right now in crypto and AI. Infinex is using NEAR Intents and chain signatures to build a single cross-chain experience. Venice AI runs private AI inference on NEAR infrastructure. Zashi wired in NEAR Intents to make onboarding and swaps into Zcash easier, right as interest in privacy-focused crypto picked back up. Wallets, AI infrastructure, privacy systems, cross-chain coordination: in each case NEAR sits underneath as the connective layer.
The market has noticed too. When Arthur Hayes, one of crypto's most-watched macro investors, started talking about NEAR, it put the network back at the center of the AI-and-infrastructure debate. His interest mattered less as a trading signal than as a sign the NEAR conversation had grown past NEAR's own community. A network once filed under “usable Layer-1 for developers” now gets discussed alongside AI agents, transaction coordination, privacy infrastructure, and autonomous finance.
The AI-and-blockchain discussion has gotten more concrete in 2026, mostly because the software has. Agents no longer just generate text. They run workflows, coordinate actions, move data between applications, and touch financial systems with real, if still uneven, independence. That changes the test for a blockchain: whether it can support autonomous systems working across fragmented environments at scale.
That shift is a big part of why NEAR is getting a second look. NEAR launched in 2018 as a high-performance Layer-1 built around usability, scalability, and hiding operational complexity from developers and users. Back then most of crypto still ran on interfaces that made people coordinate wallets, bridges, gas, and transaction routing by hand. NEAR's bet was the opposite: let the network handle that coordination in the background. Eight years later, that bet reads less like a UX preference and more like a spec sheet for AI agents.
Why NEAR Intents is becoming a major coordination layer
A lot of that attention traces back to one thing: the growth of NEAR Intents. Intents lets a user or an application state the outcome it wants instead of executing every step to get there. Which chain, which bridge, where the liquidity comes from, where execution is cheapest, all of it gets resolved underneath by the infrastructure rather than the user.
For a person, that removes most of the friction that has always made crypto a chore. For an AI agent, that same abstraction stops being a nicety and becomes a requirement. Agents are bad at clicking through fragmented interfaces and hand-coordinating five apps across three chains. They do well when they can state a goal and let the plumbing handle the rest.
And the usage is measurable, which is the part that's hard to wave away. Per SVRN and The Tie's March 2026 analysis, NEAR Intents had already coordinated more than $14 billion in cumulative volume and generated over $25 million in gross fees. By the time Sal Ternullo, SVRN's CEO, sat down for a Bankless interview, he put cumulative volume close to $20 billion. Those are real transactions and real fees, not testnet vanity numbers.
The companies building on Intents are the clearest tell. Infinex, from Synthetix founder Kain Warwick, uses NEAR Intents and chain signatures to strip out the complexity of operating across multiple chains. The goal is an experience where users never have to think about which blockchain they're on, which is the same thing NEAR has argued for since the start.
Zashi shows the privacy side of the same thesis. It uses NEAR Intents to ease onboarding into Zcash and make privacy-preserving transactions easier to reach across chains. Ternullo said on Bankless that Zashi generated several million dollars in Intents-related fees when privacy demand spiked. That is money moving through a real product, not a demo.
The pattern across all of these is the same. NEAR is becoming the layer underneath fragmented systems, coordinating transactions, liquidity, and execution so the apps on top don't have to. That job gets a lot more valuable once AI agents are the ones working those fragmented systems on their own.
Why NEAR's architecture fits the rise of AI agents
NEAR's AI story is strongest where it stays specific: execution, settlement, coordination, not sweeping claims about “decentralized AI.” On Bankless, Ternullo called NEAR “AI money,” infrastructure that lets agents transact across crypto rails, traditional payment systems, and real-world assets behind one abstracted experience. The premise is that software agents will need to move value, route liquidity, and settle across many environments, and something has to handle that.
A lot of NEAR's older design decisions line up with that premise. Account abstraction, chain signatures, low-latency execution, intent-based cross-chain transactions: each one lowers the amount of human hand-holding a system needs to act. Rather than bolting AI on as another app category, NEAR assumes agents will be first-class economic actors and builds for that.
It also explains why AI-first teams keep choosing NEAR. Venice AI uses NEAR infrastructure for private inference. Privacy is moving to the center of the AI conversation as companies realize how much sensitive financial, operational, and personal data now runs through centralized models. The deeper AI gets into enterprise and financial workflows, the louder the questions about confidentiality, ownership, and control get.
Ternullo's analogy on Bankless was cloud. Enterprises dragged their feet for years on moving sensitive workloads off-premises, worried about security and confidentiality, until the operational upside got too big to refuse. AI infrastructure looks like it is hitting the same inflection, where privacy and control start deciding which platforms win.
That is why the overlap between AI, privacy infrastructure, and blockchain coordination keeps mattering more. An agent running payments, treasury, subscriptions, or autonomous commerce has to settle transactions securely while holding onto confidentiality, permissions, and user control. Few stacks do all of that at once.
The metrics behind NEAR's momentum
What makes the momentum credible is that it registers in usage, not just price talk. NEAR points to roughly 190% year-over-year growth in application revenue, which it says led major blockchain networks over the period measured. Application revenue is a better tell than total value locked, which incentives and mercenary liquidity can inflate overnight.
The performance numbers hold up too. Benchmarking from SVRN and The Tie puts NEAR at roughly 1.2-second finality, fees under $0.002, near-100% uptime, and 1 million peak TPS in controlled tests. Those figures start to matter a great deal once agents are firing off transactions in bulk across many systems.
Plenty of chains claim fast and cheap, so speed alone isn't the argument. NEAR's edge is how closely its design philosophy matches what AI systems actually need: abstraction, coordination, and settlement that crosses chains. That fit is surfacing in wallets, privacy tools, AI infrastructure, and payments at roughly the same time.
Why NEAR's momentum feels different this time
Crypto cycles through infrastructure narratives, and NEAR has had its share of hype before. What's different now is that the momentum is tied to things people are actually using, coordination layers already carrying real volume.
The products clustering around NEAR map onto the themes shaping the next phase of digital infrastructure: AI agents, privacy, transaction abstraction, autonomous execution, cross-chain coordination. These aren't separate trends running in parallel. They are converging on the same need, for systems that can coordinate complicated digital activity automatically and out of sight.
None of this guarantees NEAR wins the category. Competition in AI infrastructure and autonomous finance is going to get fierce as more networks chase the same agent opportunity. But the current run reads less like another narrative cycle and more like years of unglamorous infrastructure work finally meeting the moment it was built for.
As agents start doing real economic work, the infrastructure under them will matter more than any narrative. The networks that win will be the ones that can hide complexity and let autonomous systems execute at scale. NEAR keeps ending up in that conversation because the things it chose to build in 2018 are the things 2026 turned out to need.
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