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InfoFi's $381M Market Decoded: How Four Verticals Are Turning Information Into Tradeable Assets

· 11 min read
Dora Noda
Dora Noda
Software Engineer

What if your ability to spot an emerging crypto trend before the crowd was worth money? Not in a vague "knowledge is power" sense, but literally — with a token price attached to your insight and a market ready to bid on it?

That's the promise of Information Finance, or InfoFi. Coined as a concept by Vitalik Buterin in his November 2024 essay "From prediction markets to info finance," InfoFi describes a class of protocols that use financial mechanisms to extract, aggregate, and price information as a public good. By early 2025, the sector had grown to a $381 million market cap. By late 2025, it had become one of the most hotly contested battlegrounds in Web3.

But InfoFi is not one thing. Beneath the umbrella term live four distinct verticals, each with its own mechanics, power players, and competitive dynamics. Understanding where each vertical stands — and where the lines blur — is essential for anyone trying to navigate this space intelligently.

The Four Verticals of InfoFi​

The InfoFi landscape can be mapped along two axes: what type of information is being priced, and who is doing the pricing. This yields four distinct market segments:

  1. Attention Markets — pricing the reach and influence of content creators
  2. Reputation Systems — pricing the credibility and trustworthiness of identities
  3. Prediction Markets — pricing the probability of future events
  4. Data Markets — pricing raw datasets, especially for AI training

Each vertical solves a version of the same core problem: in an information-saturated world, how do you separate signal from noise? The difference is which noise problem each vertical tackles.

The attention economy has been a concept in academia for decades. InfoFi makes it a market.

Attention markets tokenize influence — the ability of a voice on social media, a newsletter, or a protocol forum to shape what the community pays attention to. If you can provably demonstrate that your posts drive engagement, move token prices, or change narratives, that attention has quantifiable value.

Kaito is the most mature player here. Founded in 2022 by former Citadel quant Yu Hu, Kaito built an AI-powered platform that indexes thousands of sources — Twitter/X, forums, research papers, podcasts, news — using semantic AI to deliver a unified, ranked feed of crypto intelligence. Its "Yaps" system assigns influence scores to X accounts based on the quality and reach of their crypto commentary. By mid-2025, Kaito Pro was generating $20.8 million in annual recurring revenue — a remarkable number for a still-nascent sector.

Cookie DAO (operating as cookie.fun) entered the arena as the community counterpart to Kaito's professional-tier offering. Originally focused on AI agent analytics, Cookie DAO expanded in Q2 2025 to cover broader crypto intelligence, positioning itself as "the data layer for the agentic economy." With 20,000+ creators on the platform by late 2025, it represents the democratized, user-generated end of the attention market spectrum.

The competitive dynamic between Kaito and Cookie is not winner-takes-all. Kaito tends to serve institutional and professional researchers; Cookie DAO appeals to retail communities and AI agent operators. They are, in some sense, the Bloomberg and Reddit of InfoFi attention markets — different audiences, complementary roles.

The risk: In 2025, X's API crackdown — specifically banning apps that reward users for posting content — triggered immediate chaos. Token prices dropped sharply across attention market protocols. The sector's dependence on centralized social platforms remains its most significant structural vulnerability.

Vertical 2: Reputation Systems (Building the On-Chain Credit Score)​

If attention markets price what you say, reputation systems price who you are.

The challenge is well-known: Web3 is pseudonymous by design, which makes it exceptionally difficult to distinguish a trusted contributor from a Sybil attacker, a competent builder from a pump-and-dump promoter. Reputation systems tackle this by aggregating verifiable on-chain and off-chain signals into a credibility score — essentially, an on-chain credit rating for your identity.

Proof of Humanity (PoH) anchors the sybil-resistance layer. By combining biometric verification, social attestations, and blockchain records, PoH creates a cryptographic proof that a wallet belongs to a unique living person. By mid-2025, over 60% of top DAOs reportedly used some form of PoH for governance. The system's integration with Worldcoin and Gitcoin has significantly expanded its reach.

Lens Protocol built social graph infrastructure on top of identity, enabling reputation to be portable across applications. Rather than building a reputation on Twitter that stays on Twitter, Lens lets users carry their social history wherever they go in Web3.

Ethos Network goes further by adding a market mechanism to reputation. Launched on Base's mainnet in January 2025, Ethos creates a "credibility score" by aggregating trust signals: peer vouching, staking skin-in-the-game, and on-chain behavioral history. You can vouch for someone else's credibility — and be penalized if they behave badly. This creates economic incentives for honest reputation curation, rather than the inflationary "everyone gets five stars" problem that plagues traditional reviews.

The key insight of reputation systems: they don't just describe trustworthiness, they create it. When someone stakes real value to vouch for you, the signal is expensive to fake.

Vertical 3: Prediction Markets ($40B+ in 2025 Volume, Led by Polymarket)​

Prediction markets are the oldest and most validated form of InfoFi — they predate the term itself by decades. The premise: if you want to know the probability of an event, let people bet on it. Markets aggregate dispersed information better than polls, pundits, or panels of experts.

Polymarket is the dominant force in decentralized prediction markets. By late 2025, it had surpassed $13 billion in trading volume and held approximately $330 million in TVL. Combined with Kalshi (its regulated U.S. counterpart), the two platforms generated over $40 billion in combined trading volume in 2025 — a figure that would have seemed impossible three years prior.

The 2024 U.S. presidential election was a turning point. Polymarket's odds were cited by mainstream financial media as a real-time sentiment indicator, legitimizing prediction markets as a serious tool for probabilistic reasoning. Post-election, volume didn't collapse — it diversified into sports, science, geopolitics, and crypto-native events.

The market is not without controversy. A Paradigm analysis in late 2025 noted that most Polymarket volume analyses were double-counting by summing all order events rather than using one-sided volume metrics. The actual corrected figures are still large, but the sector's data quality issues are a real maturation problem.

Emerging challengers are entering the space with novel mechanics: some focus on AI-generated market creation, others on hyperlocal or niche event markets. The core infrastructure — AMMs adapted for binary outcomes, oracle integrations for event resolution — is increasingly modular and accessible to new entrants.

Vertical 4: Data Markets (Ocean Protocol, LazAI, and the AI Training Data Problem)​

The least visible but potentially most consequential vertical is data markets.

The premise: AI models are only as good as the data they're trained on. As the AI boom accelerated through 2025, the demand for high-quality, verifiably sourced training data exploded. The problem is that most valuable data is locked in silos — corporations, governments, and individuals hold it without mechanisms to monetize or share it securely.

Data markets provide the infrastructure for data to become a tradeable asset, with cryptographic guarantees around provenance, access control, and compensation.

Ocean Protocol is the pioneer. It enables data owners to publish datasets to a decentralized marketplace, set access terms, and receive OCEAN tokens in exchange. The protocol's focus on privacy-preserving compute — where AI models train on data without the raw data ever leaving the owner's control — makes it uniquely suited for sensitive datasets like medical records or financial histories.

LazAI represents the next-generation approach, built specifically for the agentic AI era. Its alpha mainnet, launched in 2025, introduced verifiable AI data infrastructure: datasets are hashed and committed on-chain, enabling anyone to verify that an AI model was trained on specific data without accessing the data itself. LazAI's roadmap through 2026 includes ZK-based privacy proofs, decentralized compute markets, and multimodal data evaluation systems.

The broader Blockchain AI market context: in 2024, the space was valued at $4.28 billion; projections put it at $70 billion by 2035 with a 28.93% CAGR. Decentralized AI specifically attracted over $516 million in dedicated funding through 2025, with the broader AI-crypto market cap reaching $24-27 billion.

The core problem data markets solve is the "AI data paradox": global data volumes are exploding (from 33 zettabytes to a projected 175 zettabytes over the decade), but the quality of decision-making hasn't kept pace. Data markets create pricing mechanisms that incentivize data curation, not just accumulation.

Competitive Dynamics Across Verticals​

These four verticals don't operate in sealed boxes. The most interesting dynamics are at the edges:

Attention + Reputation convergence: Kaito's influence scores are, in effect, a reputation system for information quality. As these systems mature, expect them to merge — a single score that captures both attention reach and credibility depth.

Prediction + Data interplay: Prediction market outcomes are themselves valuable data for AI training. Models trained on historical market odds can improve forecast accuracy. LazAI and similar platforms could eventually provide prediction market data as a premium product.

Reputation as gating mechanism: As Ethos and PoH systems mature, they're being used to gatekeep access to better prediction market odds, exclusive data feeds, or higher attention market weights. Reputation becomes the key that unlocks better economics across all other InfoFi verticals.

The InfoFi Thesis: Why It Matters Beyond Speculation​

Critics of InfoFi often focus on token speculation — another crypto narrative built on hype. The more interesting reading is structural: InfoFi is building the financial plumbing for the information layer of the internet.

Traditional information markets are deeply broken. Search engines optimize for engagement, not accuracy. Social media rewards outrage over insight. Expert opinions are untradeable, so there's no market mechanism to separate good forecasters from bad ones. The same credentialing systems that certify expertise are slow, expensive, and gameable.

InfoFi, at its best, creates markets that punish inaccuracy and reward genuine insight. When you stake real value on a prediction, you have skin in the game. When your reputation is on-chain, bad behavior has trackable consequences. When data is priced by the market, high-quality datasets get rewarded while low-quality noise gets filtered out.

Whether the current $381 million market cap is a floor or a ceiling depends entirely on whether these mechanisms can deliver on that structural promise — and whether the platforms can navigate the regulatory and platform-dependency risks that have already created turbulence in 2025.

The sector is young. The ideas are sound. The infrastructure is being built in real time.

BlockEden.xyz provides high-performance API infrastructure for Sui, Aptos, Ethereum, and 20+ other blockchains — the kind of reliable data layer that InfoFi protocols depend on when building real-time analytics, reputation aggregation, and on-chain data markets. Explore our API marketplace to build on infrastructure designed for the information economy.

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