Why Venice AI’s $65M Round Puts Privacy at the Center of AI

Venice AI has raised a $65 million Series A at a $1 billion valuation, marking its first external fundraise. The company’s pitch is private access to more than 200 AI models, including open source models it hosts and closed-source models it routes to through proxies.

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A mostly routine funding story with a mild Terminator lean because it emphasizes private, less restricted access to many powerful AI models amid safeguard concerns.

Why Venice AI’s $65M Round Puts Privacy at the Center of AI

Venice AI is turning demand for private, less restricted AI access into a major business. The company has raised a $65 million Series A at a $1 billion valuation, its first external fundraise, after building a service around user privacy, model choice, and a more open approach to AI responses.

The round was led by crypto-focused venture firm Dragonfly, with participation from Coinbase Ventures, North Island Ventures, and others. The raise comes as AI developers face pressure to add safeguards around mental health, personal safety, harassment, and disinformation, while many users still want broad access to what AI systems can do.

A privacy pitch with real traction

Venice AI offers access to more than 200 AI models. According to the company, users can work with models that generate text, images, audio, and video, and those models differ in performance, quality, and the amount of censorship applied.

The startup says its website already has more than 850,000 unique visitors. It also serves more than 3 million active users and an average of 1.7 million API calls per day.

That usage has translated into revenue. CEO Erik Voorhees told TechCrunch the company is already profitable, with annualized run-rate revenues of over $70 million.

The core message is simple: users want powerful AI tools, but they do not necessarily want a large platform controlling their access or storing their data. Venice AI is positioning itself as an alternative for people who value privacy and wider model choice.

How Venice AI handles models and data

Venice AI uses a mix of hosted and routed model access. It hosts open source models on its own data centers. For closed-source models, including those by OpenAI or Anthropic, it routes queries rather than hosting the models directly.

The company says all user input is encrypted and unencrypted client-side. Queries are routed through an external proxy before they are processed and returned, and Venice says no data is stored on its own systems.

Some models also support end-to-end encryption, though that feature requires a paid subscription. The structure is central to the company’s privacy-first AI platform pitch: users get access to a broad model marketplace while Venice emphasizes that it does not retain their data.

The product also highlights AI “characters” that users can customize and chat with. Venice describes its experience as “uncensored,” and Voorhees said the company works on some open models’ system prompts so they answer more openly, without adding restrictions to the models.

The safety debate around a neutral AI platform

Venice AI’s growth sits inside a larger debate over how much control AI companies should apply to their products. Concerns about AI chatbots have pushed many developers to limit or shape model behavior, especially around sensitive topics.

Voorhees frames Venice differently. Asked about access to AI models in light of recent cases of AI psychosis and resulting harm, he said the company treats its service as a “neutral tool or a neutral platform.”

He connected that idea to Bitcoin, saying: “This is the same principle that you have in Bitcoin, where Bitcoin, as a neutral protocol, works the same way for all people.” He also argued that constant monitoring would be dangerous, saying: “I think it’s actually quite dangerous from a safety perspective, for the world to enter this next phase and have everyone be constantly watched. To me that is actually much more dangerous than any particular person asking a controversial question or something that might be considered bad.”

That view is likely to remain contested. Venice is betting that user agency and privacy will matter more to a large group of customers than tighter centralized control. In Voorhees’ words: “We’re optimizing for freedom and actually respecting users as adults, which is, I think, rare these days.”

Crypto roots and token economics

The investor mix reflects the company’s background. Dragonfly led the round, and Coinbase Ventures and North Island Ventures also participated. Voorhees is an early bitcoin advocate who founded crypto companies including bitcoin gambling site Satoshi Dice and cryptocurrency exchange ShapeShift.

His privacy stance predates Venice AI. When a Wall Street Journal investigation accused ShapeShift, which initially did not require users to identify themselves, of processing millions of suspect funds, Voorhees reportedly said: “I don’t think people should have their identity recorded to catch an occasional criminal.”

Venice AI also has two crypto tokens tied to its ecosystem. It launched a token called “VVV” in early January, which Voorhees said was meant to attract users. In August last year, it added another token called “DIEM.”

Users can buy VVV and stake it to mint DIEM. DIEM generates $1 worth of AI credits per day that can be spent on Venice. Even so, Voorhees said only about 8% of the company’s users pay with crypto.

What the new funding is for

Voorhees credited Venice AI’s growth partly to the good performance of its crypto tokens. But he said the stronger driver was the company getting close to feature parity with ChatGPT.

“When we launched, we were very far away from what ChatGPT could do, but people would use us because it was private. And today, we’re very close to what ChatGPT can do […] so as we’ve closed that gap, it’s become an increasingly compelling alternative,” he said.

The next step is infrastructure. Venice AI plans to use the new funding to begin buying GPUs and building its own data centers. The goal is to stop leasing GPUs and increase gross margins.

That plan fits the company’s broader strategy. If Venice can control more of its infrastructure while keeping its privacy promise and expanding model access, it may strengthen the economic case behind its $1 billion valuation.