Data Goes Human-First: Recap of the AMA with Glint Analytics Co-CEO Ricardo Da Ros

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Key Takeaways

AI-Driven Data Insights: Glint Analytics uses AI to make blockchain data more accessible, enabling users to create dashboards using natural language.
Democratizing Access: Glint aims to lower technical barriers, allowing more people to engage with and understand crypto data.
Incentive Structure: The platform rewards verified insights instead of mere data volume, fostering a sustainable analyst economy.
Upcoming Launches: Significant milestones are on the horizon, including token generation and beta tests for new integrations on popular blockchain platforms.

Data goes human-first: AMA recap with Glint Analytics Co-CEO Ricardo Da Ros

Rewards, Web3

During a recent AMA session hosted by Cointelegraph, Glint Analytics Co-CEO Ricardo Da Ros discussed the challenges users face when extracting insights from cryptocurrency data. The session highlighted Glint’s innovative approach, which combines AI technology with human expertise to simplify data analysis. The upcoming developments for Glint, including product launches and integrations, were also a focal point of the conversation.

Transforming Complexity into Usable Intelligence

The market for blockchain analytics tools continues to grow, but many participants encounter significant technical hurdles. Da Ros attributed these challenges to fragmented data, complicated SQL tools, and premium products that primarily offer secondhand analysis.

Glint Analytics aims to break down these barriers. Their model utilizes AI-assisted, low-code solutions that allow users to create data visualizations through simple language prompts. Da Ros explained this process simply: “You ask for the data you need, Glint creates the dashboard in minutes, and an analyst adds context and conclusions.”

The concept of a “narrative dashboard” encapsulates this approach, merging context, data, and insights into a single cohesive product. After a successful Alpha launch in April 2025 and a notable win at the Solana Superteam Demo Day, the focus has remained on delivering swift, insightful analysis while minimizing user complexity. Pricing is designed to ensure broad accessibility, enabling regular users to view and vote at no cost, while pro tiers and ecosystem campaigns sustain operational expenses.

Trust, Incentives, and the Analyst Economy

The discussion then shifted to the topics of trust and incentives within the platform. Glint prioritizes rewarding verified insights over sheer data output. As Da Ros noted, “An analyst can publish thousands of dashboards, but rewards only materialize where the market identifies value."

Engagement through voting plays a crucial role in determining payouts, and the revenue generated from subscriptions, partner campaigns, and data/API access directly supports analyst rewards. Da Ros described this framework as nurturing an “analyst economy,” where both established professionals and new creators can earn compensation for valuable contributions. A points program is already in place to rank contributors and inform the reward system as it launches.

The handling of data integrity within dashboards was also elaborated on; each dashboard represents a specific moment in time, maintaining the accuracy of its accompanying analysis. Future AI developments will enable users to uncover relevant dashboards and navigate extensive content more easily, while ensuring human judgment remains central to the verification process.

What’s Next: Launch Schedule and Integrations

The launch schedule for Glint emphasizes regular delivery. The team is set to present as a finalist at the Bybit Hackathon on November 26, followed closely by the GLNT token generation event on November 27.

Earlier achievements include the winning of a Solana Superteam Demo Day and securing a grant from the Avalanche Foundation, which have bolstered the company's credibility within the developer community and blockchain ecosystems.

The platform will feature chain coverage based on user demand, with Solana and Avalanche already available to users. Hyperliquid and Monad will be included with the public beta, and NEAR is planned for future integration.

Da Ros reiterated the importance of sequencing over mere hype: “We are putting the product directly into users' hands, allowing us to iteratively enhance it based on market feedback.” He also mentioned that early community members from the Alpha period should expect to receive recognition as the complete incentive system rolls out, with further details to be shared through Glint’s official channels.