Sponsored Content

Analysis, Web3

It can take a single chart to capture a shift in the market more clearly than pages of commentary. A visualization of whale accumulation before a major price move or a breakdown of protocol revenues that challenges consensus can instantly change how a token is perceived. In that moment, raw onchain data turns into conviction, and the noise of crypto feels briefly ordered.

That instant is called a glint — the point where data becomes insight.

These glints shape trading decisions, investment theses and protocol roadmaps. They simplify complexity and connect dots across markets. Yet the people who create them, the analysts who transform data into intelligence, rarely capture the value they unlock for the market.

The recent wave of InfoFi showed that crypto is willing to pay for content. Projects funded creators and audiences consumed an endless stream of narratives. InfoFi proved the economic model around information is viable, yet it created an ecosystem where sponsored content dominated feeds and virality outpaced verification.

InfoFi’s missing layer of intelligence

At its core, InfoFi aligned projects and creators around distribution. Teams paid for coverage, creators optimized for impressions and the market learned to discount most of what appeared. Over time, a structural gap emerged between what participants needed and what the system rewarded.

Because analytical work was slower and less obviously monetizable, promotional content dominated. Millions of data points generated by emerging protocols went unanalyzed as creators focused on established projects where attention was guaranteed. There was no built-in mechanism to reward the person who dug into a protocol’s retention metrics or explored liquidity flows across chains.

The result was a disconnect as information about crypto expanded rapidly while actual intelligence lagged. Markets moved faster, and much of the onchain data that could explain those moves went unused.

Defining the analyst economy

The analyst economy reimagines InfoFi around a different unit of value: glints — concrete, data-backed insights that are demonstrably useful to traders, builders and investors.

The principle is simple. When an analyst’s work helps others make better decisions, a portion of the value created should flow back to that analyst. The model ties rewards to measurable engagement with specific pieces of analysis, routing value directly to the originators of intelligence.

Source: Glint Analytics

In this permissionless structure, analysts are free to study any protocol they consider interesting. Sponsorships do not set their agenda, and trending narratives do not dictate their work. Their analysis is open, transparent and anchored in onchain data. If a glint spreads across the market because it proves useful, the analyst is compensated for that contribution.

This is the foundation onchain intelligence platform Glint Analytics is building: an implementation of InfoFi that centers on intelligence.

What makes a glint valuable

Within the analyst economy, a glint is analysis with three clear properties:

  • Data-backed: Claims rely on verifiable onchain data, and the analysis shows its work.

  • Actionable: The insight has implications for real decisions across trading, protocol development and investment.

  • Market-validated: Quality comes from usage. Glints that traders, investors or builders use and share drive rewards.

These characteristics direct rewards toward insight that stands up to scrutiny, and they move InfoFi’s economic engine toward intelligence and durable value.

Why is this shift happening now

Several shifts make a data-backed InfoFi model viable in 2026.

In the past, analysts needed SQL skills, familiarity with complex schemas and hours of manual work to extract meaningful signals from blockchain data. AI-powered tooling can translate natural language questions into sophisticated queries, and it compresses days of effort into minutes while expanding the pool of potential analysts.

Audiences have also become far more skilled at recognizing promotional content. The collapse of the paid thread economy trained traders to be skeptical of vague narratives. Demand has shifted toward analysis that can be verified, where charts link directly to transparent data and assumptions are clearly stated.

Infrastructure now exists to sustain an analyst economy. Platforms connect analysts with audiences, measure engagement around specific pieces of analysis and distribute rewards programmatically. This infrastructure applies InfoFi’s original economic insight to intelligence.

Powering the analyst economy

Glint Analytics sits at the intersection of these trends as a dedicated platform for the analyst economy. Analysts use AI-driven tools to build dashboards and visualizations for any supported protocol without needing to write SQL. The platform abstracts away technical friction, so analytical curiosity becomes the main input.

Community, Trading
Source: Glint Analytics

Each piece of analysis published on Glint Analytics can become a glint. When traders, investors or projects engage meaningfully with that work — when they view, share or incorporate it into decisions — the originating analyst earns rewards through the GLNT token. The more useful the glint, the more it circulates and the more value returns to its creator.

Projects benefit as well. Teams focus on making their data accessible and reliable, and analysts then surface what matters most. Coverage gains authenticity because independent analysis drives it, and marketing spend plays a smaller role.

Traders gain a growing library of verifiable intelligence, and they follow analysts who consistently show their work. They anchor decisions in dashboards that reflect real onchain activity.

What changes for the ecosystem

Rebuilding InfoFi around glints and moving away from pure impressions shifts incentives across the ecosystem. Good projects with strong but undiscovered fundamentals become more visible because analysts are motivated to find them early. Weak projects become easier to challenge because their stories must survive contact with real data.

Over time, the signal-to-noise ratio improves, and analysts build sustainable businesses around their skill with blockchain data. Protocols are judged more on what is happening onchain and less on who tells the loudest story. Markets incorporate information more efficiently because high-quality intelligence remains accessible and properly rewarded.

InfoFi demonstrated that crypto will pay for content about projects. The analyst economy, as implemented by Glint Analytics, shows what happens when that same economic engine aims at data-backed insight. The premise is straightforward — when a glint creates value for the market, the analyst behind it should share in that value.

Disclaimer. Cointelegraph does not endorse any content or product on this page. While we aim at providing you with all important information that we could obtain in this sponsored article, readers should do their own research before taking any actions related to the company and carry full responsibility for their decisions, nor can this article be considered as investment advice.