Definition, Essence and Development Background of InfoFi

Source: https://docs.kaito.ai/

The core concept of InfoFi (Information Finance) is: transforming information resources that are traditionally difficult to quantify (such as project attention, KOL reputation, narrative activity, etc.) into tradable and priceable financial assets. In short, information itself becomes a “new asset” in InfoFi. This model has dual attributes of both speculative tool and signal mining tool, allowing market participants to directly speculate on information popularity while helping investors discover early signals from complex information.

Compared to traditional finance, InfoFi does not directly trade stocks, bonds, or digital currencies, but focuses on “invisible resources” such as information and attention that are not asset-based. Similar to early SocialFi (Social Finance), InfoFi also uses social media and community data for incentives, but its scope is broader and more focused on quantitative analysis of data. For example, the Yaps points system on the Kaito platform quantifies attention on social media through AI to achieve revenue distribution in SocialFi scenarios. It can be said that InfoFi is an upgraded version of SocialFi: it not only incentivizes content creation but also attempts to “redefine information value” through algorithms and incentive mechanisms, promoting structural changes in attention capital.

The rise of InfoFi is closely related to the current crypto market environment: As the Kaito platform launched the “Yap-to-Earn” mechanism and quickly gained popularity, the concept of speculative value of information itself began to spread. Subsequently, projects like Cookie DAO also released InfoFi products and incentive announcements, further pushing this concept into the mainstream. Meanwhile, traditional interactive airdrop models gradually became ineffective (early user interactions were often just arbitrage tools), and the market turned to favor new models that treat social behaviors like “who is saying what, seen by how many people” as value standards. As a result, InfoFi emerged as a new paradigm for information valorization in Web3, with project teams, users, and capital jointly driving its rapid development.

Logic and Reasons Behind the Rise of InfoFi

The rise of InfoFi is not accidental, but the result of multiple overlapping trends:

• AI Technology Empowerment: In recent years, large language models (LLMs) and natural language processing technologies have made tremendous progress, enabling the capture, analysis, and sentiment judgment of massive social media, news, and on-chain behavioral data. This technological foundation makes the quantification and pricing of information a reality, and also provides powerful backing for InfoFi platforms.
• Market Demand for New Narratives: The crypto market has always been looking for the next growth point and Alpha opportunity. InfoFi provides a new space for imagination by making “attention” and “popularity” the objects of trading. Especially under the trend of “attention precedes price”, the popularity of a project or topic is often a precursor to price movements. InfoFi attempts to make this precursor explicit, allowing investors to directly bet on information flows.
• Evolution of Airdrop Mechanisms: Traditional airdrops emphasize user interaction and usage habits, but as on-chain interactions became easily scripted, early practices gradually became ineffective. InfoFi shifts the focus from “what you did” to “what you said, who saw it”. As industry analysis suggests, InfoFi has initiated a paradigm shift: users gain “narrative rights” by spreading information, building consensus, and tokens become tools to carry consensus. In this structure, “mouth mining airdrops” becomes the native mining mode of the information age, where storytelling itself can create value.

In summary, AI technology advancement, the rise of the attention economy in the market, and the evolution of traditional airdrop models collectively gave birth to InfoFi. Ordinary investors can use this to move from the previous stages of “watching coins” and “catching trends” to a new gameplay field of pricing and trading information itself.

Representative Projects and Gameplay in the InfoFi Sector

Numerous projects have emerged in the InfoFi ecosystem. Here’s a brief overview of typical projects (sorted by representativeness).

1. Kaito

Source: https://yaps.kaito.ai/

• Mechanism and Gameplay: Kaito is the pioneer of the InfoFi concept, introducing the Yaps points system that quantifies users’ influence and content contribution on X (formerly Twitter) through AI. Users accumulate Yap scores by producing high-quality content and interacting with high-reputation accounts, then participate in platform leaderboards.
• Participation Threshold: Register a Kaito Yaps account, connect X account and link wallet; continuously publish original content and participate in community interactions.
• Potential Returns: Top-ranking users will receive allocation of platform native tokens, priority participation in IDOs and NFT subscriptions; Yaps can also be used to unlock platform features.

2. Cookie.fun

Source: https://www.cookie.fun/

• Mechanism and Gameplay: An AI-driven data panel project centered on Cookie DAO. Users can earn Snaps points by publishing content related to officially designated topics such as Spark and CookieDAO. The platform tracks indicators like mindshare, social trends, and sentiment.
• Participation Threshold: Posts on X platform need to mention designated projects or accounts and use related tags; inviting users or staking COOKIE tokens can also earn points.
• Potential Returns: Can obtain OG badges, potential airdrops, and future access to advanced features like Cookie Deep Research; higher Snaps scores lead to higher community influence ratings.

3. Galxe (Starboard)

Source: https://app.galxe.com/starboard/explore

• Mechanism and Gameplay: Galxe’s Starboard platform identifies active users through on-chain data and off-chain behavior, combining AI sentiment analysis and user-submitted content to generate Aura reputation scores.
• Participation Threshold: Produce quality content related to partner projects (such as Plume, 0G, Dango) on Twitter, or continue to participate in Galxe’s traditional interactive tasks.
• Potential Returns: Users with high Aura will receive project-specific rewards (NFTs, tokens); Galxe will also set participation thresholds for more quality events based on Aura scores.

4. Ethos Network

Source: https://app.ethos.network/

• Mechanism and Gameplay: Ethos is an on-chain reputation system that builds a decentralized “credibility score” through community evaluations (positive, neutral, negative), endorsement mechanisms, and trust/distrust vote trading.
• Participation Threshold: Users can evaluate others, vote on evaluations, endorse behaviors, and participate in reputation predictions in Ethos Markets.
• Potential Returns: Improve one’s own credibility score to gain trust resources; speculate on trust votes or XP rewards through the market to participate in airdrops; establish long-term reputation identity assets.

5. Noise

Source: https://www.noise.xyz/

• Mechanism and Gameplay: Noise is an attention index trading platform based on data streams like Kaito, allowing users to speculate on the attention trends (mindshare) of crypto projects with high leverage, rather than token prices themselves.
• Participation Threshold: Invitation required to enter the platform, then select targets in the mindshare market for trading.
• Potential Returns: If you judge that a project’s attention will rise, you can position early in the mindshare market to enjoy the price difference brought by high leverage. Currently in testing phase, airdrop plans may be announced later.

6. GiveRep

Source: https://giverep.com/

• Mechanism and Gameplay: A SocialFi protocol based on the Sui chain that converts users’ behaviors on Twitter (posting, interactions, tagging) into on-chain reputation assets $REP, forming Trophy Score and Reputation Point.
• Participation Threshold: Tag @GiveRep when posting tweets, or participate in specific projects’ Loyalty Program plans.
• Potential Returns: Points can be exchanged for REP or partner project tokens; establish multi-dimensional on-chain identity profiles for long-term community recognition or specific airdrop qualifications.

Overall,
Kaito is more geared towards professional users: its Yap points are based on content influence, leaning towards top KOLs, with a relatively black-box algorithm;
Cookie takes a community approach, with its Snaps combining content quality and user loyalty, encouraging long-term participation focused on a single project;
Cookie has publicly disclosed its scoring rules (high transparency), and data mainly comes from the X platform, while Kaito integrates multiple data sources (Twitter/Discord/on-chain) and offers paid access to advanced analytics. These two represent different paths of professional and community-oriented InfoFi respectively.
In addition to the above projects, new players in the InfoFi sector continue to emerge, such as Wallchain, MirraAI, XHunt, QuoteChain, DexCheck, etc., each adopting different data sources or incentive models to enrich the ecosystem. Overall, these projects innovate around quality content contribution, attention trading, reputation assessment, and other directions, providing users with multiple participation paths.

Typical Paths for Retail Investors to Participate in InfoFi

Ordinary users who want to get a piece of the InfoFi sector can approach it in several ways:

• Create content to earn points (Write-to-earn): The best way to participate in most of the above projects is to continuously produce quality content and earn points. For example, posting tweets, writing in-depth posts, etc., on platforms like Kaito, Cookie, Galxe can accumulate corresponding Yaps, Snaps, Aura, and other points. This method has a relatively low cost (mainly investing time and brainpower) and is quite sustainable. However, it’s important to note that reputation scores can be inflated or manipulated, so learn to distinguish between genuine KOL opinions and “fake” noise, avoiding blindly following the crowd.
• Directly trade information assets: If you have strong judgments about certain events or project trends, you can directly trade attention shares or reputation scores on platforms like Noise and Ethos. This is similar to speculating on information indices or social sentiment. In such trades, speed and accuracy are crucial, requiring close attention to market dynamics and decisive execution.
• Assist investment decisions: Even if not directly betting on InfoFi platforms, the data they generate can be helpful for investments. For example, using Kaito’s search and rankings, Ethos’s reputation scores, etc., as a “crypto investment data panel” can assist in judging project quality and community heat. InfoFi tool data often reflects market sentiment and consensus preferences, and reasonable use can increase information advantages.
• Project investment: Focusing on early-stage projects in the InfoFi sector itself and selecting potential tokens for medium to long-term investment is also a path. Research team backgrounds, technical routes, community ecosystems, and token economic models, early layout for reward pools has high-risk, high-return characteristics. As the sector matures, some leading project tokens may have good value growth potential.
• Interact and participate for airdrops: Closely follow the dynamics of emerging InfoFi projects, actively participate in their testnet interactions, community activities, and content contributions to obtain early airdrops. This is a zero-cost way to get involved. Many InfoFi projects invite community participation in testing or experimenting with new features before launch, often distributing airdrops or early token rewards to active users.

The above participation paths have different focuses: content creation-based gameplay is the most widespread; information trading and decision-making gameplay are more suitable for users with a certain level of expertise; investment and testnet participation lean towards medium to long-term or community interaction. Retail investors can choose suitable paths and combine them according to their interests and resources.

Pitfall Avoidance Guide for the InfoFi Sector

While InfoFi brings many new opportunities, it also comes with risks and traps that need to be vigilant about:

• Information overload and echo chambers: When using InfoFi tools, you’ll encounter a lot of derivative data. Don’t fall into new “information cocoons” or “echo chambers”, avoid only listening to algorithm-pushed opinions. Actively seek different voices and maintain critical thinking.
• Focus on real interactions and community quality: Be wary of projects with severe inflation of numbers and unhealthy discussions. Real discussions usually have diverse voices and technical depth, while fake heat is often piled up by a large number of bot accounts. Carefully observe the quality of accounts behind discussions: is it real users spontaneously communicating, or marketing statements from unified templates? This is crucial for judging the authenticity of InfoFi projects.
• Identify “inflated” projects: Any project oriented towards “points” or “increasing presence” can be artificially manipulated. Carefully read project whitepapers and announcements to understand if the points rules and incentive mechanisms are reasonable and transparent. Try to participate in projects with open mechanisms and sufficient community supervision (such as DAO governance).
• Maintain independent judgment: The data and rankings provided by InfoFi platforms are only reference tools, final decisions should be based on your own research. Avoid following the crowd, you can actively read analyses that differ from mainstream views and compare information sources horizontally. Remember, information “hype” may precede value realization, blindly following trends often carries great risk.
• Do due diligence: In the InfoFi sector, you still need to “read whitepapers, watch roadshows”. Understand details such as the project’s team, technical architecture, token economics, and community governance. Only with sufficient understanding of the project itself can you reduce participation risks.

In short, becoming a rational “information prospector” requires staying sober and cautious while embracing new opportunities.

Future Development Trends and Industry Impact of InfoFi

InfoFi is sparking new industry thinking about information value, and its future development may be reflected in integration with other fields and the emergence of new mechanisms:

• Synergy with DeFi: For example, Ethos Network’s on-chain reputation scoring has the potential to become a credit reference for DeFi lending. Users with high reputations can enjoy lower borrowing rates or better collateral ratios; while DeFi’s quantitative strategies can also use real-time sentiment indices and popularity trends provided by InfoFi platforms as trading signal inputs.
• Linkage with SocialFi: In the InfoFi environment, the value of content creators’ Social Tokens can be priced more fairly. On one hand, InfoFi platforms quantify creators’ attention and influence, turning their social behaviors into tradable equity; on the other hand, this also provides new channels for “being seen” and revenue generation for mid-tier creators in the community.
• Integration with AI: AI Agents can act as active participants in the InfoFi market, such as automated information arbitrage and risk hedging. In the future, AI-centric prediction markets or intelligent investment research systems may emerge, feeding InfoFi data back to other ecosystems. It’s foreseeable that AI will not only be the driving force of InfoFi but will also become a participant in it.
• Organized narratives and consensus mechanisms: Some analyses point out that in the InfoFi era, “information is the air layer of consensus”. In the future, project teams and communities may more consciously “organize” narratives: building topics and designing content incentives through community collaboration, making narratives spontaneously become productivity. Tokens then become carriers of narratives, with information flows and value flows more tightly coupled.

In summary, InfoFi will have a profound impact on empowering user data sovereignty and expanding the boundaries of the attention economy. As the sector matures, we may see more mechanisms characterized by community co-governance and data openness, making information production and distribution fairer and more diverse. For ordinary retail investors, understanding the essence of InfoFi, using tools wisely while avoiding risks will be key to grasping the next wave of Alpha.