Welcome to the first network for user-owned data



r/datadao is a community-owned data collective focused on Reddit data. It is the largest data DAO in history, with 140k users.


Volara is a decentralized data marketplace for X data. Run a miner to earn rewards.


Flirtual empowers users to take control of their dating app data, transforming it into valuable insights and opportunities

Block Explorer

View details of data transactions, addresses, and other activities on the Satori testnet.


Fund your testnet wallet to start developing and experimenting with user-owned data applications.

The Foundation for Decentralized AI

What is Vana?

Vana is a distributed network for private, user-owned data, designed to enable user-owned AI. Users own, govern, and earn from the AI models they contribute to. Developers gain access to cross-platform data to power personalized applications and train frontier AI models.

Data Liquidity

AI models are only as powerful as their training data, which is held by centralized platforms despite being legally owned by each user. Data Liquidity Pools (DLPs) incentivize, aggregate, and cryptographically verify valuable data, liberating data from walled gardens to push the frontiers of AI.

Start a pool
Non-Custodial, Portable Data

Vana makes data portable and non-custodial. Users log in with their wallet, and all their data is there, just like their funds. This paradigm of non-custodial data allows for next-level experiences, like giving an LLM deep, personal context without compromising privacy.

Build with non-custodial data
Open Infrastructure

Vana originated as an MIT research project in 2018, focused on enabling users to own their data and the AI models they create. It is entirely open source and operates as a permissionless, decentralized network. The Open Data Foundation is dedicated to driving mass adoption of the Vana protocol, while other contributing organizations, such as Corsali, focus on research and development.

Run a node

We believe in an open internet where users own their data and the AI models they contribute to.

AI models should be created more like open source software: iteratively by a community. To make this possible, researchers need access to the world's best datasets that are held captive across walled gardens. Users can break down these walled gardens by exporting their own data.

We are building towards a user-owned AI foundation model, trained by 100M users who contribute their data and compute.

Accelerating Towards User-Owned AGI

Technical Foundation
  • First Onchain Training Data, 2021
  • Non-Custodial Data Patent, 2022
  • Personal Server Architecture, 2022
Early Adoption
  • Data Portability MIT Hackathon, 2023
  • User-Owned Personal AI, 2023
  • Local LLM with Personal Data, 2023
Scale and Decentralize
First Data DAO, 2024
Decentralize Data Infrastructure
16 Independent Data DAOs
Mass Adoption
  • Onboard 100M Users
  • Aggregate World's Largest Training Dataset
  • Train User-Owned Foundation Model