Oasis Just Went Live With Private AI. Here’s What PAI3’s Already Doing Better.

Jennifer OwhorJennifer Owhor
3 min read

In a quiet but significant launch, the Oasis Protocol Foundation rolled out ROFL Mainnet, a framework for verifiable off-chain compute built for AI applications. It’s the latest milestone in a fast-evolving space we now know as DeAI: decentralized, privacy-preserving AI infrastructure.

ROFL makes a bold promise, run AI computations off-chain, keep them private, and still prove they happened correctly. It’s a milestone in building trustable intelligence.

But here’s what you may have missed, while Oasis just launched, PAI3 is already running.

And it’s not only verifying compute, but also rewarding it.

Privacy as Infrastructure

If 2023 was the year of AI hype, 2024–25 is clearly the year of AI infrastructure rethinking its trust model. Centralized APIs are fast, but not private. Black-box inference is powerful, but unverifiable. For anyone building AI agents that interact with sensitive data, that’s a dealbreaker.

The ROFL mainnet answers that with TEEs (Trusted Execution Environments) that allow you to run AI off-chain and prove it was done correctly — without exposing the data.

PAI3 answers it differently.
By turning the compute itself into a public mesh. By encrypting the agent task, routing it through a permissionless network of nodes, and rewarding the nodes that run those tasks privately.

In both cases, privacy is the protocol.

What PAI3 Is Already Doing

While Oasis leans into off-chain trust proofs, PAI3 focuses on fully decentralized AI execution:

  • You can deploy your own private agents — permissioned, encrypted, and monetizable.
  • You can run tasks through a live global network of nodes — with every task earning real rewards.
  • You can use real data (safely) — without fear of surveillance or third-party retention.

In other words, PAI3 is already delivering the future.

What This Means for Builders

For those building in AI right now, agents, workflows, vertical automation, private copilots, there’s a clear trend emerging:

You can’t keep building on centralized models that store every prompt, own every insight, and shape every output.

You need infrastructure that lets you:

  • Own your logic
  • Protect your users
  • Prove nothing was tampered with
  • And still scale with real-world usage

Oasis and PAI3 represent different ends of the same solution set. Oasis proves it happened. PAI3 lets it happen, privately and openly and pays contributors for it.

Oasis ROFL arrived at a moment when:

  • Major AI APIs are rate-limiting and usage-tracking
  • Enterprise teams are demanding verifiable privacy
  • The next wave of AI apps require real trust and **composable infrastructure

    **

PAI3 doesn’t compete with this shift, rather it reinforces it. It’s the active layer where agents live, work, and transact without surveillance, lock-in, or vendor dependence.

The Path Forward: Build on What’s Already Working

The infrastructure is live.
The agents are running.
The incentives are aligned.

If Oasis just proved private AI is possible, PAI3 proves it’s economically viable for builders, contributors, and anyone participating in the AI economy directly.

The future of AI is permissionless, private, and peer-to-peer.

Explore more: pai3.ai/earn — Run private compute, earn from task routing
pai3.ai/docs — Build and deploy your first agent
@Pai3Ai on X — Active updates, partnerships, and community drops

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Written by

Jennifer Owhor
Jennifer Owhor