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Traffic to meaning, without the maze of SQL – that set the tone of the Cointelegraph AMA with Glint Analytics. Co-CEO Ricardo Da Ros framed the company’s thesis in simple terms: “AI accelerates the process, humans validate results, and incentives enforce quality.”
The session walked through why most users still struggle to extract insight from crypto data, how Glint’s model closes that gap, and what the next two weeks mean for launch velocity.
Democratizing On-Chain Data: AI, Incentives and the Future of Crypto Analytics with Glint Analytics [Brought to you by @GlintAnalytics] https://t.co/RmnAEiqIyh
— Cointelegraph (@Cointelegraph) November 19, 2025
From complexity to usable intelligence
The market for blockchain dashboards keeps expanding, yet average participants still face high technical barriers. Da Ros traced that to fragmented data, SQL-heavy tools, and paywalled products that encourage consumption of secondhand analysis.
Glint’s approach removes the technical entry point through AI-assisted, low-code tooling that builds charts from natural language. He summarized the workflow clearly: “Ask for the data you need, Glint assembles the dashboard in minutes, and an analyst adds context and conclusions.”
The team calls this a “narrative dashboard” – context, data, and insight presented as one artifact. Early validation came with an Alpha launch in April 2025 and a win at Solana Superteam Demo Day 2025, which helped the team prioritize speed to insight and keep complexity behind the scenes.
Pricing aims to keep access broad: Da Ros said regular users can view and vote for free, while pro tiers and ecosystem campaigns fund operations.
Incentives, sustainability, and the analyst economy
The conversation moved to trust and incentives. Glint rewards verified insight rather than volume. According to Da Ros, “An analyst can publish a thousand dashboards, but rewards only accrue where the market sees value.”
Voting and engagement determine payouts, and revenue – subscriptions, partner campaigns, and data/API access – funds analyst rewards. Da Ros framed this as seeding an “analyst economy”: a venue where professionals and emerging creators get paid for getting calls right. A points program already ranks contributors and feeds the reward logic for launch.
Glint also clarified data handling inside dashboards. Each dashboard captures a snapshot in time to preserve the integrity of the accompanying analysis; the team may explore live views later if they align with the model. On the AI side, Glint will extend its engine to help users discover relevant dashboards and navigate large content sets, keeping human judgment central to verification.
Launch window, integrations, and what’s next
Glint’s November cadence underscores delivery. The company pitches as a Bybit Hackathon finalist on November 26, followed by the GLNT token generation event on November 27.
Prior milestones include a Solana Superteam Demo Day win and a grant from the Avalanche Foundation, which helped anchor credibility with builders and ecosystems.
Chain coverage reflects user demand and current activity. Solana and Avalanche are available today. Hyperliquid and Monad arrive with the public beta, and NEAR sits on the roadmap.
Da Ros emphasized sequencing over hype: “We put the product in people’s hands and iterate with the market.” He added that early community members from the Alpha period should expect recognition as the full incentive system goes live, with details to follow on Glint’s channels.
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