Covalent binds centralized systems and decentralized systems, treating blockchains like databases that can be queried and indexed. Unlike traditional databases, Covalent focuses on making blockchain data accessible in a decentralized fashion, acting as middleware that bridges the gap between blockchain infrastructure and existing workflows like Excel.
Covalent faced significant market and financing risks during its early years, especially during the bear market of 2018-2019. The team bootstrapped without external capital and struggled to find product-market fit. Additionally, there was technology risk, but they benefited from the dominance of EVM (Ethereum Virtual Machine) in the blockchain space.
Covalent's unified API allows developers to access data from over 200 blockchains with minimal changes. For example, switching from Ethereum to Solana or Polygon requires just one character change in the API call. This eliminates the need to rebuild the stack for different chains, making it highly efficient for developers.
Covalent provides structured data, which is essential for training large language models (LLMs) and AI applications. Its extensive historical and real-time Web3 datasets enable use cases like on-chain copy trading, fraud detection, and predictive analytics. Covalent's data is foundational for AI models in the Web3 space.
CQT (Covalent Query Token) is a staking and governance token that underpins Covalent's decentralized economy. Revenue from developers using Covalent's API is used to buy back CQT, which is then distributed to node operators. This creates a flywheel effect, incentivizing long-term data availability and participation in the ecosystem.
Covalent's decentralized indexing offers cryptographic security, ensuring that every data mutation is auditable. This level of trust is crucial for advanced use cases in crypto. Centralized indexers, while they may gain some traction, lack the same security guarantees and often fail to sustain long-term viability in the Web3 space.
Covalent is seeing significant trends in data availability (DA) and AI, with a growing focus on structured data for training models. Additionally, liquid staking tokens (LST) and restaking mechanisms are gaining attention. Covalent remains focused on its core expertise in data and AI, avoiding speculative trends.
Covalent aims to drive revenue through its unified API, Gold Rush block explorer, and Increment dashboarding product. The company is also capitalizing on the growing demand for historical blockchain data, with partnerships like Infura driving traffic to Covalent. The focus is on expanding use cases and improving data accessibility.
Welcome to another episode of WEB3 Founders Real Talk! Get ready for an enlightening discussion with Ganesh Swami, the CEO of Covalent, as he unveils Covalent's product development progress and strategic plans for revenue generation, lists AI model use cases empowered by Covalent, and shares noteworthy trends in the cycle. Tune in now for an episode that promises both insight and inspiration!
00:25 Introduction of Ganesh and Covalent
05:39 Challenges & Resistance
10:13 Differences with Other Data Solutions
14:49 How the Flywheel Works
18:14 Product Development Progress
20:18 Use Cases of AI models
24:13 How CQT Plays Within the Ecosystem
27:58 Strategic Plan for Revenue Generation
31:35 Viewpoint on Centralized Data Indexing
35:56 Notable Trends
39:30 Two Thoughts
Disclaimer: This channel is for informational purposes only and should not be construed as investment advice. All the opinions expressed by channel guests are solely their own opinion and do not represent either【WEB3 Founders Real Talk】or Mint Ventures in any way. WEB3 Founders Real Talk将对话Web3海内外项目的创始团队,为大家带来最直观的创业故事分享。 本期我们邀请到Covalent的CEO Ganesh Swami,他将揭晓Covalent的产品开发进展和针对收入增长的战略计划,列举由Covalent赋能的AI模型使用案例,并分享这个周期中值得关注的趋势。
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重要声明:主持人或者嘉宾在播客中的观点仅代表他们的个人看法。此播客仅用于提供信息,不作为投资参考。