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The average trader in the cryptocurrency space needs to query and analyze blockchain data to identify patterns and make informed decisions. Yet, accessing comprehensive blockchain research is usually a costly and fragmented process. Paywalled dashboards, premium subscriptions and private data rooms put reliable insights out of reach for most, while analysts themselves rarely see fair compensation for their work.
Glint, a blockchain intelligence project, solves this by bringing analytics onchain. Its model allows insights to be funded and shared within the community, creating a more open and fair environment for crypto analytics.
In an interview with Cointelegraph, Glint co-founder Dhruv Chaturvedi explains how this model works, what role AI plays in it and the team’s plans for the early phase.
Cointelegraph: What’s broken about how crypto analysts are paid today, and what behaviors does it create?
Dhruv Chaturvedi: Most analysts don’t get paid for their work on the incumbent Web2-based Web3 analytics platforms. Outside of one-off bounties or commissioned research, there’s no direct reward for consistently producing or sharing insights. This bounty-based system makes crypto analytics a reactive process — analysts only contribute when there’s a short-term incentive, not because the data itself is valuable.
As a result, insights stay private or vanish into social media threads. Glint flips this model by rewarding ongoing contribution and transparency; our mission is to turn crypto analytics and insight sharing into a proactive, self-sustaining process.
CT: How do you plan to introduce non-fungible tokens (NFTs) to improve ownership and monetization of insights for analysts?
DC: Each published dashboard can be minted as an NFT, giving its creator verifiable authorship and a tradable claim to its future rewards. The primary functionality begins during each reward epoch, when the community votes through their interactions — sharing, liking or upvoting dashboards and charts. The NFT holder (the creator) earns directly from the value their work contributes back to the network, as determined by community voting.
Beyond that, creators will also receive ongoing rewards whenever their queries or data sets are called by the Glint API to power external applications, such as AI agents.
CT: From publishing a dashboard on Glint to getting paid, how does the process work?
DC: Publishing on Glint feels just like Web2, except you don’t need SQL. It’s AI-first, so analysts can create dashboards simply by describing what they want in natural language. Once generated, they can save and publish with a single click, just like any traditional analytics tool. But behind the scenes, the dashboard is minted onchain, with all Web3 functionality handled seamlessly in the background.
Then, when any other users like, share or upvote a dashboard, those interactions are recorded onchain as well and essentially act like votes. An autonomous smart contract tallies these interactions at the end of each weekly epoch, calculates the value contributed by each creator into a score and distributes rewards automatically based on that score.
The rewards are paid directly to the wallet the creator connected to Glint.
CT: When a dashboard is minted as an NFT, and what rights and royalties do creators retain?
DC: The creator — or rather, the holder — of the NFT earns perpetual royalties whenever their queries or dashboards are used by the Glint API. This ensures they maintain a continuous share of revenue tied to the ongoing utility of their work.
While we haven’t yet opened a marketplace for trading these NFTs, that’s something we’re exploring. In theory, creators could sell their Glint Dashboard NFTs, along with the rights to future rewards, on any Web3 marketplace. It will be interesting to see what value the top creators’ dashboards can command in these scenarios!
We’re also experimenting with allowing other creators to fork or reuse specific charts or components from existing dashboards. In such cases, a share of the secondary dashboard’s rewards would automatically flow back to the original creator, creating a layered, collaborative economy where innovation and reuse are both rewarded.
CT: How does your onchain voting and reward design deter Sybil attacks, vote buying and engagement farming?
DC: We’re realistic — in the early stages, some gaming of the system is inevitable anywhere money is involved. Initially, our team will manually oversee the reward logic, reviewing interaction histories, wallet patterns and onchain behavior to flag duplicate or suspicious activity. This allows us to refine the anti-Sybil mechanisms and fine-tune the contract rules before full decentralization.
Over time, these responsibilities will transition to decentralized autonomous organization (DAO) governance. The community will ultimately decide how the reward contracts operate — including parameters that prevent vote manipulation, farming and other exploitative tactics. The goal is to evolve from a guided system into one that’s entirely self-governed, resilient and community-policed.
CT: What is the role of the AI component on Glint?
DC: The AI component removes the technical gate that SQL has long created in blockchain analytics. Instead of writing complex queries, users can simply describe what they want, for example, “show me the top wallets accumulating SOL this week,” and the AI generates the chart or visual. It builds, formats and optimizes queries, connects relevant data sets and returns what it finds back in the form of a visual insight.
Right now, it’s already performing better than most tools we’ve seen, but it’s constantly learning and improving. If the output isn’t perfect, users can still jump in and manually edit the SQL to fine-tune results — nothing is locked away. Over the coming months, we expect the AI to evolve beyond generating single charts, allowing users to create entire dashboards from just a prompt or two. We want to make analytics on Glint truly conversational.
CT: How do you ensure data quality and reproducibility over time?
DC: Well, actually, the data on Glint is primarily from external sources — around 90% of it is blockchain data, which, obviously, can be verified at any time onchain. We see ourselves as an aggregator of reliable onchain data providers, along with selected off-market data sources, such as CoinGecko.
CT: As you transition to DAO governance, which parameters will the community control first and what milestones lead to full governance?
DC: The first phase will give tokenholders control over reward weights and reward contract rules, allowing them to decide and govern payouts. Next comes grant allocation for data integrations. Full governance will expand to treasury management, model-training priorities and protocol parameters once the reputation and voting system stabilize, but this is all way down the line — we’re focused on the road to mainnet launch right now!
CT: What are the details of your public beta? Who are the first 100 analysts and first 1,000 users you aim to onboard during this phase?
DC: Our public beta launches next month with live dashboards, AI-powered queries and tokenized rewards. The first supported chains will be Avalanche, Solana, Polygon and Hyperliquid, with additional integrations — including offchain data sources — following soon after. The first 1,000 users — primarily traders, DeFi builders and researchers — will earn early access points that will later convert to GLNT tokens.
CT: Looking ahead, what does the onchain intelligence space look like when AI agents are ubiquitous and dashboards are tokenized, and where does Glint sit in that future?
DC: We would like to see Glint becoming a foundational visualization and verification layer for the DeFAi economy. As AI agents and trading tools become more autonomous, they’ll rely less on traditional visuals and charting and more on instant, trigger-based data, but accuracy will matter more than ever. In such a world, AI hallucinations could be catastrophic for decision-making and capital allocation.
Glint’s network of human-verified and validated queries will form a trustworthy database of Web3 intelligence. That human-verified layer — powering both agents and human users — is what we believe will anchor the next generation of AI-assisted trading and data systems.
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