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Vana (VANA): tokenomics, risks and score

44/100SCORE · DCaution Grade D, caution

A chain where users pool their personal data into collectively owned datasets and receive tokens representing ownership, with AI companies paying to train on them.

What Vana is, and what it does

This is an AI or compute network. It coordinates machine learning work, hardware or data across many independent participants instead of one company's data centre.

What the VANA token itself does: It can be staked to earn rewards, though a large part of those rewards is newly issued token rather than earned revenue.

Where it runs: Vana. Mechanism: Proof of stake for user owned data pools. It has been running since 2024, so roughly 2 years.

The facts

TICKER
VANA
SECTOR
AI and compute
CHAIN
Vana
LAUNCHED
2024, so around 2 years of operating history
MECHANISM
Proof of stake for user owned data pools
MAXIMUM SUPPLY
120 million
VALUE CAPTURE
Staking only
UPGRADE CONTROL
Team controlled
VESTING
Heavy overhang
LIQUIDITY BAND
Micro cap. Thin, often a single venue or pool. Treat the quoted price as indicative only.

How the score breaks down

track record7/20
tokenomics11/20
transparency15/15
decentralisation5/15
adoption3/15
liquidity3/15

Each dimension is explained on the directory page, and the reasoning behind it is taught in the Academy research process.

Supply and value capture

A hard maximum supply that cannot be raised without the agreement of essentially every participant. Holders can stake to earn rewards, though much of that reward is newly issued rather than earned revenue.

The founding team retains control over upgrades or parameters. Ownership is heavily concentrated. A small number of wallets hold enough to determine the price on their own.

Where it is strong and where it is not

✓ Strengths
  • Supply is capped, so holders are not diluted indefinitely
  • Audited, with published reports
  • Fully open source, so the code can be independently reviewed
✗ Weaknesses
  • Heavily concentrated ownership means a few wallets control the outcome
  • Significant supply is still scheduled to unlock, which is a structural headwind
  • Upgrade control sits with a small group, so the rules can change
  • Thin liquidity. Check order book depth before assuming you can exit

Incident history

No major exploit, collapse or regulatory action on record against this asset.

Our read

It addresses a real and growing question about who owns the data AI models are trained on and who gets paid for it. Whether AI companies will pay for pooled consumer data when they currently scrape it for free is the unproven part of the thesis. Very new with heavy unlocks.

The main risk

The core assumption, that AI firms will pay for data they currently obtain free, is unproven.

Before you buy anything

Check the contract address against the project's own documentation rather than a search result or a screener link, since impersonation tokens with identical names and logos are listed constantly. Check the order book depth before assuming you can exit at the quoted price. And write down what would make you wrong before you buy, not after. The Academy thesis module covers why that single habit protects more capital than any indicator.

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RISK WARNING Crypto assets are highly volatile and largely unregulated. You can lose everything you put in. Nothing on this page is financial, investment or tax advice, and nothing here is a recommendation to buy or sell any asset. Do your own research and never commit money you cannot afford to lose.