Crypto Analytics Transforms with AI-Driven Dashboards: An Interview with Glint

Summary:
Glint, a blockchain intelligence project, aims to reshape crypto analytics by providing onchain insights powered by AI. In an insightful interview, co-founder Dhruv Chaturvedi discusses the limitations of current analysts' compensation models, the innovative use of NFTs for ownership of analytics, and the future of decentralized governance.

Key Takeaways:

Current State of Crypto Analytics: Most analysts struggle to get fairly compensated for their work on existing platforms, resulting in a lack of proactive contributions.
NFT Integration: Glint uses NFTs to provide creators ownership and profit-sharing from their dashboards, enabling continuous revenue generation.
AI Utilization: The platform simplifies dashboard creation through natural language prompts, eliminating the need for complex coding.
Decentralized Governance: Future governance will shift to a community-controlled model, overseeing reward structures and contract regulations.
Public Beta Launch: Glint's public beta is set to launch soon, allowing users to interact with AI-powered analytics and earn token rewards.

Crypto analytics goes onchain with AI-first dashboards — Interview with Glint

The Need for Comprehensive Crypto Analytics

In the dynamic world of cryptocurrency trading, users must frequently analyze blockchain data to spot patterns for informed decision-making. However, accessing thorough blockchain research often involves high costs and fragmented resources. Premium subscriptions, paywalled dashboards, and private data rooms hinder many traders from obtaining reliable insights, while analysts frequently do not receive adequate compensation for their efforts.

Glint addresses these challenges by delivering onchain analytics. This innovative approach fosters community funding and sharing of insights, promoting a more equitable landscape for crypto analytics.

Insight from Glint’s Co-Founder

Cointelegraph: What issues currently exist in how cryptocurrency analysts are compensated, and what behaviors does this foster?
Dhruv Chaturvedi: Many analysts find themselves unpaid for their contributions on traditional Web2 platforms handling Web3 analytics. Typically, rewards come from one-time bounties or commissioned projects, which fails to incentivize ongoing contributions. This causes insights to remain hidden or get lost within social media threads.

Glint changes this narrative by encouraging regular contributions through transparent rewards, aspiring to make crypto analytics a proactive, sustainable process.

Enhancing Ownership and Monetization with NFTs

CT: What is your strategy for incorporating non-fungible tokens (NFTs) to enhance ownership and monetization for analysts?
DC: Each dashboard published can be minted as an NFT, granting its creator verified authorship and the ability to trade future rewards. During reward epochs, the community votes via their interactions—likes, shares, or upvotes—allowing NFT holders to earn based on their contributions determined by these votes.

Additionally, creators will secure ongoing rewards each time their data sets or queries are utilized by Glint's API for external applications, including AI agents.

Dashboard Publication Process

CT: Can you explain how the process of publishing a dashboard on Glint works, from creation to compensation?
DC: Publishing on Glint is akin to using traditional Web2 tools but without needing SQL knowledge. Our AI-driven platform allows analysts to generate dashboards by simply describing their requirements. They can save and publish with a click, while the system handles all Web3 logistics seamlessly. Engagements with these dashboards are also logged onchain, functioning as a voting mechanism.

At the end of each weekly epoch, an automated smart contract calculates contributions and distributes rewards to creators based on their score.

Rights and Royalties of NFT Creators

CT: When is a dashboard minted as an NFT, and what rights and royalties does the creator retain?
DC: NFT holders earn ongoing royalties whenever their queries are utilized via Glint’s API. This model guarantees that they retain a share of revenue linked to the continuing value of their contributions.

While a marketplace for these NFTs is not yet available, we are exploring the potential for creators to sell their dashboard NFTs and associated future rewards on Web3 platforms. Additionally, we hope to facilitate collaboration by allowing other creators to use parts of existing dashboards, ensuring that original creators still receive a portion of any resultant rewards.

Deterring Malicious Engagements

CT: How does your voting and reward structure prevent Sybil attacks and engagement manipulation?
DC: We acknowledge there may be attempts to exploit the system early on. Initially, our team will oversee reward mechanisms manually, reviewing interaction histories and wallet behaviors to identify anything suspicious. This will help us adjust our anti-Sybil strategies before full decentralization.

Eventually, these responsibilities will transition to a decentralized autonomous organization (DAO), wherein the community will govern how reward contracts function, implementing measures to deter vote manipulation and unfair practices. The vision is to evolve into a fully governed, resilient system that the community polices.

The Role of AI in Glint

CT: What is the significance of AI in Glint's operations?
DC: AI reduces the complexity historically associated with blockchain analytics. Instead of dealing with intricate queries, users can simply articulate their requirements, like “show me the top wallets accumulating SOL this week,” and the AI produces the relevant visuals. It efficiently organizes queries, connects datasets, and presents insights visually.

Currently, it's outperforming many existing tools and is continuously improving. If users aren't satisfied with the AI's output, they can manually edit the SQL to enhance results. Over time, we expect the AI's capabilities to expand, enabling users to build entire dashboards from minimal prompts, making analytics more conversational on Glint.

Ensuring Data Quality

CT: How does Glint maintain the quality and reproducibility of its data?
DC: Most data on Glint, around 90%, comes from verifiable blockchain sources. We position ourselves as aggregators of reliable onchain data providers alongside a select number of off-market sources, such as CoinGecko.

DAO Governance Plans

CT: As you transition to a DAO governance model, which parameters will be addressed first, and what milestones will you pursue towards full governance?
DC: Initially, stakeholders will gain control over reward structures and contract rules. Subsequently, they will govern grant allocations for data integrations. Full governance will expand to include treasury management and protocol parameters once the voting and reputation systems stabilize, but for now, our focus is on preparing for our mainnet launch.

Upcoming Public Beta Details

CT: What can you share about your public beta and the initial user onboarding plan?
DC: We will launch our public beta next month, featuring live dashboards, AI queries, and token-based rewards. The initial supported networks will include Avalanche, Solana, Polygon, and Hyperliquid, with additional integrations to follow. Our primary goal is to bring 1,000 early users from trader and DeFi developer communities, granting them access points that will later convert to GLNT tokens.

Future of Onchain Intelligence

CT: Looking ahead, what do you envision for the onchain intelligence landscape when AI agents and tokenized dashboards become commonplace, and what role will Glint play?
DC: Our aim is for Glint to become a foundational layer of visualization and verification in the DeFi-AI economy. As AI tools and trading instruments grow more autonomous, the demand for precise, immediate data will heighten. In this future scenario, inaccuracies could drastically impact decision-making and capital allocation.

Glint’s database of human-verified queries will provide a trustworthy foundation for Web3 intelligence. This layer of verified insight—supporting both AI agents and human users—is anticipated to be essential for the next generation of AI-assisted trading and data analysis systems.