What InfoFi actually means
The name is ungainly, so start with the literal translation. InfoFi is short for information finance. The category borrows from the older idea of DeFi, or decentralized finance, which turns money into programmable building blocks, and applies the same logic to information itself.
The pitch is simple. On crypto Twitter (now X), Farcaster, YouTube, and Discord, attention is the scarcest resource. Hundreds of thousands of accounts post, debate, and shill every day. Most of that activity disappears into a firehose that no human can read. InfoFi projects step into that firehose with two moves.
First, they measure attention. AI agents scrape posts, replies, quote tweets, video views, and follower graphs, then assign each account a numerical score that reflects how influential it has been over the last seven days, the last 24 hours, or even the last hour.
Second, they turn that score into a tradable object. That object can be a leaderboard rank that pays out a reward pool, a token whose price moves with the underlying score, or a market where users bet on which projects will be trending next week.
So when someone says AI InfoFi, they mean the overlap of two things. The AI is the layer that measures attention at scale, including natural language processing, social-graph analysis, and increasingly large language models. The InfoFi part is the financial wrapper that turns those measurements into tokens, leaderboards, and prediction markets.
The whole thesis is that attention has economic value and that value should be priced, traded, and redistributed, instead of being captured for free by platforms and a handful of influencers.
The honest risk picture (early)
InfoFi is roughly two years old as a category, and the data so far is mixed. Before you look at any specific token, the risks are worth naming in plain English.
The biggest risk is that attention is not a cash flow. A mindshare leaderboard can rank a KOL, or key opinion leader, at number one for 30 days in a row, but if no protocol earns revenue from that attention, there is no underlying stream of dollars supporting the token. This is the same structural problem that hit social tokens in the 2021 cycle. Hundreds of creator coins launched, almost all of them lost 90 percent or more of their value within a year, and most are now unlisted.
The second risk is that the attention signal can be bought. Coordinated groups can inflate a project's mindshare score by paying dozens of accounts to post, reply, and engage in a coordinated window. AI scoring helps detect this, but the arms race between sybil farms and detection algorithms is constant. Leaderboards in 2024 and 2025 have already shown obvious manipulation patterns around airdrop seasons, where accounts that suddenly rank at the top of a project have zero historical footprint outside that project.
The third risk is platform dependency. Most InfoFi metrics are scraped from X and Farcaster. If those platforms change their API rules, throttle scraping, or simply deprioritize crypto content, the data feed breaks. A leaderboard whose underlying signal disappears has no value at all.
The fourth risk is reflexivity. InfoFi tokens often pump when a project trends, and the trending itself is partly caused by the token pumping. This feedback loop is real, but it cuts both ways. When sentiment turns, the same loop accelerates the drop.
The fifth risk is regulatory. Several InfoFi tokens have been scrutinized for looking like unregistered securities, especially when they distribute rewards to top-of-leaderboard holders. None of the major protocols have been shut down, but the legal picture is not settled.
None of these risks mean InfoFi is doomed. They mean the asset class is genuinely new, the cash flows are not proven, and a non-trivial slice of the tokens in this category will probably go to zero.
How InfoFi works mechanically
Strip away the marketing and InfoFi is a stack of three layers, each built on top of the last.
The bottom layer is the data layer. This is the raw stream of posts, replies, video views, podcast mentions, and on-chain actions (wallet moves, contract deploys, governance votes) that an InfoFi protocol wants to track. Most protocols ingest from X via the official API, from Farcaster via the Hub, from YouTube via public transcripts, and from on-chain indexers like Dune or Nansen. The richer and cleaner this layer, the more trustworthy the layer above it.
The middle layer is the scoring layer. This is where AI earns its place. A scoring engine takes the raw data and asks: who is talking about this project, how often, with what sentiment, with what credibility, and with what audience reach. Output is typically a numeric mindshare score per project per time window, plus a sentiment label (bullish, neutral, or bearish) and a credibility weight per account. Cookie.fun publishes a public methodology that scores KOLs and projects across several dimensions. KAITO runs an AI research terminal that produces similar outputs. Snaps focuses on Farcaster-specific data.
The top layer is the financial layer. There are three common shapes.
Shape one is a leaderboard with a reward pool. Protocols like Cookie.fun and Snaps publish a weekly or daily ranking of the top mindshare contributors. A portion of the protocol's token supply is distributed to top-ranked users. This is essentially a payroll for attention, paid in tokens rather than dollars.
Shape two is a mindshare token. A token is launched whose supply is partially or fully tied to the project's attention metrics. If the mindshare score goes up, the token gets burned or minted in a way that should, in theory, capture the rising attention. KAITO is the cleanest public example of a token explicitly priced as an attention index.
Shape three is a prediction market on attention. Users bet on which project will trend next week, which KOL will rise or fall in the ranking, or whether a token's mindshare will cross a threshold. This shape is less common so far, but several InfoFi projects have teased it for late 2025 and 2026.
The three layers stack into a complete loop. Data flows in, AI scores it, finance wraps it, and the resulting prices and rewards feed back into the data layer as more people talk about the project to chase the rewards.
The three live protocols: KAITO, Cookie.fun, and Snaps
Calling them the big three is a stretch, since the entire category is still small. They are the three most visible InfoFi projects in mid-2025 and each takes a different angle on the same idea.
KAITO is the broadest. Launched in early 2025, KAITO pitches itself as the AI x crypto information layer. Its main product is a research terminal that aggregates crypto news, social signals, on-chain data, and AI-generated summaries. KAITO also runs a mindshare index for hundreds of tokens, which assigns each token a relative attention score. The KAITO token itself is the attention-index token: it is marketed as a way to get exposure to the broader crypto attention economy rather than to any single project. The token has been volatile, with multiple 50 percent drawdowns between launches and major unlocks.
Cookie.fun is more focused on the KOL economy. Its public dashboard tracks every meaningful crypto account on X, scores them with an AI that weighs post quality, audience credibility, and engagement authenticity, and publishes a daily leaderboard. Top-ranked KOLs earn a share of COOKIE token emissions. The platform also runs project-level mindshare scores, which some traders use as an alt-data signal for early trend detection. Critics point out that the COOKIE token has had limited real revenue and that much of its price action has been tied to airdrop speculation.
Snaps is the smallest of the three and the most focused. Built on Farcaster, Snaps rewards users for posting about specific crypto projects. Each project can launch a Snap campaign with a reward pool, and users earn by contributing high-quality posts, measured by an AI scoring system that looks at originality, engagement, and audience quality. Snaps is essentially a programmable bounty system for attention, and its mechanics are the closest analog to legacy creator-economy payouts of the three.
These three are not the only InfoFi projects. Others include Galxe's mindshare layer, KAITO-powered dashboards embedded in partner protocols, and a handful of mindshare tokens that launched in 2025 with similar pitches. None have the liquidity or longevity of the big three yet.
How InfoFi compares to the legacy creator economy
InfoFi is often pitched as Web3's answer to the creator economy, so it is worth comparing directly to what creators earn today.
In the legacy model, a creator's income comes from a small set of platforms. YouTube pays out roughly 55 percent of ad revenue to creators. Twitch pays roughly 50 percent of subscription revenue. Spotify pays fractions of a cent per stream. Substack and Patreon take 10 percent of paid subscriptions. TikTok's creator fund has been criticized as underfunded and inconsistent. Across all of these, the platform takes a meaningful cut, the algorithm decides who gets surfaced, and the creator has no claim on the underlying audience data.
InfoFi tries to flip this. The promise is that attention is measured on open data, scored by open AI, and rewarded by open token emissions. No platform middleman. No algorithm gatekeeper. The reward goes directly to the wallet of whoever earned the attention.
The upside is real. KOLs in emerging markets, where bankrails are weak, can earn tokens that are globally tradable. Projects can launch attention campaigns without negotiating with YouTube or TikTok. Audiences can see exactly which creators drive the most engagement and reward them transparently.
The downside is also real. Legacy creator payouts are denominated in dollars, euros, and yen, currencies that actually buy groceries. InfoFi rewards are denominated in tokens that can drop 80 percent in a quarter. The headline APY of 1,200 percent on a leaderboard means nothing if the underlying token loses 90 percent of its value during the same window.
There is also a maturity gap. YouTube has spent 15 years building creator tooling, copyright systems, and brand-safety frameworks. InfoFi has spent two years building leaderboards. The infrastructure for long-term creator careers is thin.
For an actual working creator, the practical answer in 2025 is hybrid. Use YouTube, Twitch, and Substack for dollar-denominated revenue. Use InfoFi protocols for speculative upside and for the social signal that comes with high leaderboard rankings. Do not put your rent on InfoFi token emissions.
The critique: real revenue vs. pure hype
The honest critique of InfoFi fits in one sentence. Most InfoFi tokens do not yet have a real revenue stream, and their prices are driven almost entirely by attention.
That sentence is uncomfortable for the category's biggest proponents, because it is largely true.
Cookie.fun does not charge a fee on the trades its leaderboard indirectly drives. KAITO's terminal is free for most users and the protocol's treasury revenue, where it exists, comes mostly from token unlocks rather than product fees. Snaps charges a small fee on campaigns, but campaign volume is a small fraction of the fees that flow through a real exchange.
Compare that to a protocol like Hyperliquid, a perpetuals exchange, which generates hundreds of millions of dollars in fees annually and uses those fees to buy back its token. Or Uniswap, which collects a small fee on every swap and routes it to token holders. Those are real cash flows.
InfoFi's argument is that the cash flows will come later. The analogy used by founders is to Bloomberg terminals: free at first, expensive once institutional users are hooked. The risk is that the analogy is wrong. Bloomberg had a monopoly on financial data for decades. InfoFi competes with free X search, free Farcaster clients, and free AI summaries from ChatGPT and Claude. There is no obvious reason why a fee-paying InfoFi terminal will win that fight.
The other defense is that mindshare is itself a leading indicator of price action. If a token's mindshare triples in a week, the chart often follows. So InfoFi tokens are valuable as tradable signals, regardless of cash flow. This is true, but it is also a fragile edge. As more traders see the same signal, the alpha decays, and the signal becomes self-fulfilling until it is not.
A fair summary: InfoFi has a real product (AI-scored attention data) and a real market (crypto KOLs chasing leaderboard rewards). It does not yet have a real business model at the protocol level. Most of the tokens in this category are priced as if the business model will exist in two years. Some will be right. Many will not.
Practical implications if you want to participate
If after all of that you still want exposure to InfoFi, the practical playbook in 2025 looks like four moves.
First, separate signal from token. You can use InfoFi dashboards (Cookie.fun's leaderboard, KAITO's terminal) as free research tools without owning any InfoFi token. This is the lowest-risk way to participate.
Second, if you do buy a mindshare token, treat it as a venture-style bet, not a stable allocation. Size positions small, expect 70 to 90 percent drawdowns, and assume most tokens in this category will be illiquid within 18 months.
Third, watch the unlocks. InfoFi tokens have aggressive unlock schedules, and supply inflation has been the single biggest drag on prices in 2025. Read the tokenomics before you buy.
Fourth, watch for revenue. The InfoFi project that wins long term will be the one that builds a real fee business. Until then, the category is largely a sentiment trade.
A final note on safety: none of these protocols are FDIC-insured. None are regulated as securities in most jurisdictions. None will reimburse you if the smart contract is exploited. Counterparty risk on the exchanges that list these tokens is also real. Treat the position size accordingly.
How to follow InfoFi the smart way
InfoFi moves fast and so does the news around it. Tracking mindshare scores, leaderboard shakeups, and AI scoring methodology changes manually is a losing game for most traders. Zippfeed surfaces InfoFi headlines with sentiment scoring (bullish, neutral, or bearish) and an importance rating, so you can spot which attention signals actually matter before the rest of the market catches up.
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