🔐 Inside Venice: Building the Private AI Economy—How VVV & DM Tokens Power Permissionless, Sovereign Inference

🧭 Why Private AI Matters—and Why Venice Exists

The foundational thesis behind Venice is deceptively simple: if the thought of everything ever typed into an AI model being published publicly makes someone pause, privacy isn't optional—it's essential. According to John, head of strategy at Venice, and Jesse, the CTO, the company was built on the principle that "it's somewhat dystopian that a small handful of tech companies are building databases of everybody's most intimate thoughts."

As AI agents and models grow more capable, users are feeding them increasingly sensitive data—health records, proprietary code, business strategy, personal thoughts. All of this ends up stored on centralized infrastructure controlled by companies like OpenAI, Anthropic, or xAI. The risk isn't necessarily that these companies are malicious, but that rogue employees, hackers, or government subpoenas could expose that data—intentionally or not.

Venice's answer: build a mass-market consumer AI app where privacy is a core tenant, not a feature. Most Venice users aren't crypto natives. Many actively dislike tokens. But they use the product because it works—and because they value control over their data.

"It's not about whether you have something to hide. You want a place where you can think and not have to worry about constantly being observed." — Jesse, CTO of Venice

📊 The Market Opportunity: Consumer AI with Privacy Baked In

Venice isn't targeting a niche. The addressable market is every consumer globally. The company views itself not as a "private AI" player, but as a consumer household AI brand—one that happens to prioritize privacy. When people think of AI, Venice wants to be mentioned in the same breath as ChatGPT and Claude.

The hook? Two foundational pillars:

• Privacy: Zero data retention, no post-training on user inputs, and local on-device memory storage.
• Unrestricted Access: No content moderation committee deciding what the AI can or cannot say. Users get "raw machine intelligence" without refusals or moralizing responses.

This combination has proven effective. Many users arrive at Venice after hitting content restrictions on other platforms—asking benign questions only to be refused or redirected. These friction points drive organic growth, as frustrated users search for alternatives that "just work."

Another competitive edge: model aggregation. Venice consolidates access to hundreds of AI models—open-source and closed-source—into a single, consistent interface. Users don't need multiple subscriptions or fragmented workflows. Prompts, memories, and data persist across sessions. The platform even anonymizes requests to closed-source models like Grok, offering state-of-the-art inference with zero data retention through commercial agreements with providers like SpaceX.

"Nobody wants to have 15 different AI subscriptions in the same way that we're all frustrated that we have to have 15 different subscriptions to stream movies." — John, Head of Strategy

🤖 Agentic Chat: Removing Cognitive Load from Model Selection

One of Venice's most significant recent product launches is Agentic Chat, which eliminates the need for users to manually select models. The system routes queries intelligently across text, image, video, audio, and music models—choosing the best tool for each task behind the scenes.

Only about 20% of legacy Venice users engaged with the model selector. For most, the choice between GLM 5.1 and Kimmy 2.5 was overwhelming—even for those inside the industry. Agentic Chat solves this by making model selection invisible. The result? Conversion from free to pro users doubled compared to the legacy product.

This aligns with Venice's broader strategy: aggregate the value of all open-source models, reduce friction, and deliver a superior user experience without requiring deep technical knowledge.

💰 The VVV and DM Token Economy: A Financial Primitive for Compute

Venice's tokenomics represent one of the most thoughtful implementations of utility tokens in recent crypto history. At the core are two tokens:

• VVV: Staked to mint DM. Acts as the foundational asset in the ecosystem.
• DM: A tokenized unit of inference. One DM equals $1 worth of compute per day, perpetually, as long as it's staked.

The system works as follows:

1. Users lock VVV to mint DM via a bonding curve.
2. The mint cost adjusts dynamically based on a target rate—currently set at 38,000 DM.
3. As more DM is minted, the cost to mint additional DM rises. If DM is burned (unlocking VVV), the mint cost falls.

This creates a market-based equilibrium where users choose whether to mint DM or buy it on secondary markets, depending on which is more economically attractive at any given time. Venice influences—but does not control—the supply, adjusting the target rate to balance utilization and liquidity.

"DM is a kind of new financial primitive that lives on-chain. It's tokenized inference that can be used by other DeFi applications or anyone who wants to build on top of it in all sorts of interesting ways." — Jesse, CTO

This financialization layer is intentional. Venice is actively supporting third-party developers building on top of DM—creating reseller apps, lending markets, and structured products around compute. The result is an ecosystem, not just a product.

🔄 The Growth Flywheel: How Revenue Fuels the Token Economy

One of the most elegant aspects of Venice's model is how product usage directly benefits token holders. Every time a user:

• Signs up for a pro subscription
• Purchases credits on the platform
• Uses the API

...a portion of VVV is bought and burned, reducing supply and creating deflationary pressure.

This means Venice can attract non-crypto users—many of whom actively dislike tokens—and still have their usage contribute to the token economy. The product experience is decoupled from the tokenomics, but the two reinforce each other downstream.

John notes that most Venice users are not crypto people. They don't care about VVV. But their subscriptions and usage drive demand for the token regardless. This is a rare example of a crypto project where price appreciation correlates with product adoption, not just speculation.

📈 Recent Growth: What's Driving the Surge?

Venice has experienced significant growth over the last two months, visible on-chain through VVV burns tied to new user signups. Four key factors explain the surge:

1. Grok Integration: Private access to Grok—especially its video models—has driven substantial new user growth. Venice doubled the number of generations in May compared to April, which itself had doubled from March.
2. Asian Market Expansion: Venice began activating markets in Korea and other Asian regions, filling demand gaps during US nighttime hours and maximizing inference utilization.
3. Agentic Chat Launch: The new interface has been rolling out over the last 45 days and is now the default experience. It converts to paid at 2x the rate of the legacy product.
4. Token Attention: Increased focus on VVV itself has created a self-reinforcing loop—price attention drives product curiosity, which drives usage, which drives revenue, which drives burns.

"Having been in crypto for quite a while, it's really nice to be working on a product where when the crypto side of things gathers more attention due to price or whatever, it actually reinforces the product itself." — Jesse, CTO

🤝 Agents as First-Class Citizens: Protocolizing Inference

Venice treats AI agents as consumers. The platform is explicitly designed to be agent-first—meaning agents can autonomously purchase and use inference without human intervention.

Key design principles:

• Permissionless access: Agents can acquire DM on-chain and use it without identity verification or account setup.
• Perpetual inference rights: DM gives agents a known, fixed amount of compute over time—critical for autonomous operation.
• API-native: The Venice API is designed so agents can "just point at Venice and it works," whether using OpenClaw, Claude Code, or other frameworks.

Jesse frames it philosophically: "For agents, inference is existential. They don't exist without it." Agents are inference. This makes DM particularly valuable in an agentic economy—agents may be willing to pay far more for compute than humans, because for them, it's the cost of existence.

Venice has mandated internal use of agents across the team since the beginning of the year, dogfooding the product to optimize for autonomous use cases. The result is a platform where pointing an agent at Venice and saying "do this thing" simply works.

🏛️ Regulatory Posture: Privacy as a Human Right

Venice's leadership—many of whom come from ShapeShift, where they fought high-profile regulatory battles—approaches compliance with a clear ethos: build for users, defend their rights.

So far, the US has been one of the best places in the world to build an AI company, especially compared to its past hostility toward crypto. But if that changes, Venice is prepared.

"We're never looking for a fight. But people know Eric. People know his ethos. We're not afraid to stand up for what we think is right." — John, Head of Strategy

Jesse adds that Eric is "one of the most principled and honest founders" he's ever worked with—a rare trait in entrepreneurship, and one that permeates Venice's culture.

🎯 Final Takeaway: A Token Economy That Actually Works

Venice represents something uncommon in crypto: a functional token economy built around real product utility. The relationship between VVV, DM, inference demand, and user growth is not abstract—it's mechanical, measurable, and self-reinforcing.

The team isn't chasing speculators. They're building a household AI brand that prioritizes privacy, user experience, and permissionless access—attributes that happen to align perfectly with decentralized infrastructure and tokenized compute.

For anyone watching the intersection of AI and crypto, Venice is a case study in how to do it right: lead with product, embed crypto where it adds value, and let the token economy emerge organically from real demand.

"The more usage of the product that happens, the more it actually helps the token economy. The bigger the product, the more of a revenue stream Venice has, the better for all token holders." — Jesse, CTO

🔗 Venice is proving that privacy, performance, and tokenomics can coexist—and that the future of AI doesn't have to be dystopian.