HomeCryptoTokensAI and compute › OPEN

OpenLedger (OPEN): tokenomics, risks and score

44/100SCORE · DCaution Grade D, caution

A chain where data contributions to AI models are attributed and rewarded whenever the resulting model is used.

What OpenLedger 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 OPEN token itself does: It receives a share of the fees the protocol collects, so holding it is a claim on real revenue.

Where it runs: OpenLedger. Mechanism: Chain for attributable AI data and models. It has been running since 2025, so roughly 1 years.

The facts

TICKER
OPEN
SECTOR
AI and compute
CHAIN
OpenLedger
LAUNCHED
2025, so around 1 years of operating history
MECHANISM
Chain for attributable AI data and models
MAXIMUM SUPPLY
1 billion
VALUE CAPTURE
Fee share
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 record5/20
tokenomics13/20
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. A share of protocol fees reaches holders directly, which is the strongest form of value capture available.

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
  • The token captures real protocol revenue rather than relying on speculation alone
  • 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

Attribution of training data to ongoing model revenue is the correct answer to one of the genuine fairness problems in AI, and doing it at the protocol level is more rigorous than doing it contractually. Whether AI developers adopt a system that obliges them to pay for data is the open question. Heavy unlocks.

The main risk

Depends on AI developers voluntarily adopting attribution obligations, and unlocks are heavy.

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.

COMPARE
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.