🔥 Near's Privacy-First AI Stack Is Quietly Eating The Competition

💡 The Big Picture: Privacy, Intelligence, and Commerce Are Merging

The evolution of crypto infrastructure is no longer just about faster transactions or lower fees — it's about fundamentally reimagining how humans and agents interact with value. Near Protocol is building across three critical pillars: Near Intents for crosschain execution, Near AI for confidential inference, and Near.com as the consumer-facing interface that unifies it all.

As crypto matures from speculative token plays to real revenue-generating companies, projects like Near are being evaluated not on narratives, but on fundamentals: revenue, user adoption, and sustainable business models. Near is leaning into this shift with tangible metrics and a verticalized approach that brings disparate technologies under one roof.

"Near Intents has done over $23 billion in volume. That is getting over to Near.com. You've got all the great things around AI, agentic economy, agentic commerce happening on Near.com as well. Truly competing on both the financial side as well as the frontier technological side with respect to AI."

📊 Near Intents: The Crosschain Execution Layer Gaining Momentum

Near Intents has emerged as a credible crosschain execution layer, processing significant volume while maintaining a focus on user experience and privacy. Key metrics highlight its traction:

• Intent volume: Over $23 billion processed
• Revenue: Approaching $40 million
• Monthly net revenue: Around $253,000
• Unique users (last 30 days): 550,000
• Revenue as % of Near emissions: Approximately 10%

These figures demonstrate that Near is not just building infrastructure — it's monetizing it. The revenue dashboard (available at revenue.near.org) offers real-time transparency into how the protocol is capturing value, a critical signal as the market increasingly demands cash flow visibility alongside token price action.

🧠 The App That Ate The Stack: Near.com's Unified Vision

Matt Henderson, a builder in the Near ecosystem, articulated the vision behind Near.com: a single financial app where users see all their assets in one place — Bitcoin, Zcash, USDC, and eventually real-world assets like ETFs and stocks — without caring which chain they originated from.

"In Near.com, since we're built on Near Intents, you just see all of your assets in one place... It's just all there together. And in the future, we'll be having real world assets, ETFs, stocks, bank accounts, and it will begin to... you won't really know if you're dealing with a crypto app or a real world financial app."

This approach eliminates chain-level friction, a persistent UX barrier in crypto. Users shouldn't have to understand bridges, gas tokens, or liquidity fragmentation. They should express an outcome, and the infrastructure should handle the rest.

Henderson emphasized simplicity and empathy as core design principles. Onboarding a friend into crypto revealed how confusing wallet ecosystems remain for outsiders. Near.com aims to abstract away jargon and technical complexity, meeting users where they are rather than forcing them to learn a new language.

⚡ Intents vs. AMMs: The Capital Efficiency Trade-Off

The panel featuring representatives from Cow Swap, Kyber Swap, and Near Intents explored the trade-offs between intent-based protocols and traditional automated market makers (AMMs).

Tyler Bond from Near Intents articulated the core advantage of intents:

"AMMs are really good because they're always on, but they're extremely capital inefficient... It's the complete opposite for intents and for solvers where you have this extreme capital efficiency because all you need is a market maker to come on and say, 'Yeah, I'm going to provide liquidity for this one asset.'"

However, intents have a vulnerability: liquidity providers can step back during volatile periods, leaving users without execution options. AMMs, while capital-intensive, provide passive liquidity that's always available.

Felix from Cow Swap highlighted coincidence of wants as a key network effect:

"Users that are trading at the same time get batched together into the same kind of execution problem, and then they act almost as liquidity providers for one another... Batched intent systems really have these positive network effects that the more people use them, the higher the efficiency gains are."

This is where agent-driven economies become compelling. If agents execute more frequent, smaller trades on behalf of users, the probability of matching opposing flows increases dramatically, reducing reliance on external liquidity providers.

🛡️ Privacy Is No Longer Optional — It's Infrastructure

The privacy panel featuring Zcash, Dash, Starknet, and Near underscored a critical theme: privacy is becoming a first-class infrastructure primitive, not an afterthought.

Daniel from Zado framed it clearly:

"Agents don't care, guys. They're not like humans. They have no allegiances. They want to use the best tech... They want to use the tools that allow them to be the best versions of themselves. They've got no allegiances to Bitcoin, to Zcash, to Near, to Starknet."

Key developments in privacy infrastructure include:

• Zcash's Orchard pool: Encrypted money at scale, now usable via Near Intents and other integrations
• Dash's shielded pool: Live on mainnet, based on Zcash's Orchard technology, with one-second confirmations and 20-second wallet syncing
• Starknet's protocol-level privacy pool: A canonical pool where any asset can be shielded, enabling anonymous interaction with any app via helper contracts
• Near's confidential intents: Selective disclosure model that balances user privacy with regulatory compliance

Dylan from Near Intents explained the practical privacy approach:

"We're happy to work with law enforcement agencies and partners when needed. We look at it as practical privacy where a user doesn't want their activity tracked or linked... At the same time, we don't want to be a Tornado Cash or a mixer."

This "practical privacy" model — confidentiality by default with selective disclosure mechanisms for legitimate law enforcement — may represent the regulatory middle ground that allows privacy tech to scale without being shut down.

🤖 AI Agents: The Inevitable Shift in On-Chain Activity

The vision of an agentic economy is no longer speculative. Multiple panelists described a near-term future where agents handle the majority of on-chain transactions, from swaps to staking to complex DeFi strategies.

Cameron from Near AI outlined where agentic commerce stands today:

"Right now, agentic commerce is for digitally native things. Things like APIs, agents paying other agents to do certain crypto-related tasks... We're starting to see examples with Mercury and Brex, smart routing... We're doing smart remittance with Abound, where an agent calls an API to get a foreign exchange price to do remittance at the best rate."

However, security remains the biggest bottleneck. The AttackBench benchmark, developed by FailSafe in collaboration with Near, revealed that existing agent frameworks are highly vulnerable to adversarial attacks. Prompt injection, confused deputy problems, and subverted reasoning remain unsolved at scale.

Ari from FailSafe emphasized the need for objective evaluation:

"The motivation we had was that most of the stuff we saw were just a bunch of static tests... In practice, attackers have been leveraging LLMs and doing intelligent attacks and actually seeing the inference that's being done by the other side."

The solution is defense in depth: multiple layers of security, including permissioning, sandboxing, hardware-backed trust execution environments (TEEs), and continuous adversarial testing.

🔐 Confidential AI: Privacy-Preserving Intelligence at Scale

The panel with Intel, Brave, and Near AI explored how private model routing and confidential computing are becoming table stakes for enterprise AI adoption.

Przemas from Near AI explained the value proposition:

"If you want to run the best models locally, this is going to cost you tens of thousands of dollars of upfront cost... We offer the same guarantees as running models locally but in the cloud. You as a customer have a cryptographic proof that there is no way for Near or any privacy-preserving solution to actually see your prompts and the responses from these AI models."

Key insights from the confidential AI discussion:

• TEEs (Trusted Execution Environments) from Intel provide hardware-backed guarantees that data and workloads are protected during execution
• Near AI serves as a backend for Brave Leo, Brave's browser-based AI assistant, with confidential inference
• Privacy is becoming a business necessity, not just a user preference, as enterprises realize the liability of exposing sensitive data to LLM providers

Luke from Brave noted a shift in demand:

"When you really start to see this stuff kick in, it's when businesses have to be concerned because it really... and they should be. All these different contexts in which people are using these things become liabilities across the board."

💸 The Future of Payments: Stable Coins, Intents, and Nano Transactions

The final panel with Circle and Near AI explored how stablecoins, intents, and AI agents are converging to reshape payments.

Gordon from Circle highlighted the growth of X42, an interoperability protocol where the vast majority of settlements occur in USDC. While transaction volume remains modest, the protocol has processed millions of transactions, demonstrating demand for nano payments — small-value transfers that traditional payment rails cannot economically support.

George from Near AI emphasized that privacy, confidential inference, and secure agent harnesses are the three critical primitives for a functional agentic economy:

"If you take a step back and you have transaction infrastructure that's capable of being private, you have inference that's capable of being private and secure, and you have agents that are capable of being private and secure, we think those three components are the key three components of building a powerful, valuable, private, and secure agent economy."

One major unsolved problem: chargebacks. If agents make mistakes — and they will — how do users recover funds? Traditional finance has chargebacks and dispute mechanisms. Crypto does not. Solutions may include escrow contracts, identity-linked slashing mechanisms, and insurance pools, but these are still in early design phases.

🚀 What's Next: A Composable, Privacy-First Future

Near's strategy is ambitious: verticalize the stack, own the user experience, and provide infrastructure that works for both humans and agents. This means:

• Near.com as the consumer interface, abstracting away chain complexity
• Near Intents as the execution layer, handling crosschain swaps, staking, and yield
• Near AI as the intelligence layer, with confidential inference and private model routing
• Confidential balances and private send features coming to Near.com
• Integration with tokenized equities via Robinhood Chain and other RWA platforms

The ultimate vision: agents don't care what chain they're on. They care about outcomes. Near is building the infrastructure that makes outcome-based execution seamless, private, and economically rational.

As the market shifts from narrative-driven speculation to revenue-driven fundamentals, Near is positioning itself as a real business with real metrics. With confidential intents, private AI, and a unified consumer app, Near is betting that privacy, intelligence, and liquidity are the three pillars of the next wave of crypto adoption.

"The term crypto might be fading a bit into the background. Just kind of the same way that no one says, you know, we're an internet company anymore. Like all companies are internet companies. So, it feels like the blockchain world and the financial world are merging." — Matt Henderson, Near.com

The question is no longer if this future arrives. It's how fast — and whether Near can maintain its early lead as agents, institutions, and users converge on a privacy-first, chain-abstracted financial stack.