Interview with Footprint Analytics CEO

Footprint Analytics is devoted to making a structured information platform that bridges the hole between Web2 and Web3 information.

We concentrate on structuring information. Regardless of the relative benefit of Web3 over Web2 in clear on-chain information, sure challenges stay. These embrace the nascent standing of the business, a scarcity of standardized practices, and a scarcity of organized information. Consequently, information software turns into problematic.

As an instance, take into account the state of affairs the place you wish to entry transaction information on Opensea from a number of chains similar to Ethereum, Solana, and Polygon. This course of entails understanding OpenSea’s enterprise mannequin, learning sensible contract code, and sequentially extracting transaction information from every chain.

This course of is sophisticated. At first, it’s sophisticated and vulnerable to errors all through the information assortment course of. Second, it’s technically complicated, given the variations in ledger design and information constructions throughout chains. Lastly, it results in a waste of assets. In a state of affairs the place 1,000 folks want this information, they’d should undergo a equally complicated course of 1,000 instances. This important repetition considerably hinders information assortment effectivity and wastes computing assets.

This brings us to the aim of Footprint Analytics: to summary information from disparate sectors similar to GameFi, NFTs, and DeFi and set up standardized information practices for the Web3 business. This, in flip, will allow builders and business contributors to entry and analyze information effectively and precisely.

To this point, we’ve launched platforms on greater than 20 blockchains, organized into three core segments:

1. Footprint Progress Analytics as an Trade Answer: Tailor-made options for Web3 initiatives in advertising and marketing progress and operational analytics, much like a Web3 model of Google Analytics, driving initiatives in direction of data-driven progress.
2. Zero-Code Knowledge Evaluation Instruments: Offering an expertise much like ChatGPT, this software permits customers to acquire information evaluation reviews by easy queries and responses. Within the foreseeable future, the usage of on-chain information will likely be vastly simplified – no sophisticated understanding of Web3 enterprise logic or superior programming abilities will likely be required, streamlining the transition from Web2 to Web3.
3. Free Unified API: By means of a unified multi-chain and cross-chain API, this function facilitates cross-chain information entry throughout a number of chains, offering customers with a seamless expertise to retrieve information from a number of chains for free of charge.

As a knowledge platform, Footprint is a pure match with AI. AI encompasses three key sides: computing energy, information, and algorithms. Amongst these, computing energy is the inspiration that underpins AI mannequin coaching and execution. On the identical time, information is the essence of AI, and algorithms dictate AI efficiency, together with mannequin accuracy and software effectiveness.

Of those, information is undoubtedly an important and indispensable. Knowledge is the lifeblood of industries and initiatives, and its significance extends to key areas similar to privateness and compliance, the place its worth is immeasurable. Knowledge could also be past buy, given its involvement in privateness and compliance points. AI acts as each a shopper and a producer of information.

At the moment, Footprint’s software of the convergence of information and AI encompasses a number of main points:

Through the information content material technology section, the contribution of AI inside our platform is essential. Initially, we use AI to generate information processing code, offering customers with a extra streamlined information evaluation expertise.

Extra particularly, we’re driving innovation in two particular instructions.

First, we’re curating and categorizing reference information. Taking just lately deployed contracts on the blockchain for example, our AI can autonomously decide the protocol to which a contract belongs, the kind of contract, and even whether or not the contract falls underneath classes similar to LP or Swap on Dex platforms. This clever structuring and classification vastly improves information accessibility.

Second, we will generate higher-level area information primarily based on our reference information. For instance, we use AI to create information inside domains similar to GameFi, NFT, and many others., offering customers with richer information assets. This strategy enhances the standard of information content material and permits customers to raised perceive information throughout totally different industries.

To enhance the front-end consumer expertise, now we have launched an AI-based clever evaluation operate. As talked about above, when customers interact Footprint for information evaluation, they encounter an expertise much like a dialog with ChatGPT. Customers can ask questions and instantly obtain corresponding information evaluation reviews. The underlying logic entails translating textual content into SQL queries, dramatically decreasing the entry barrier for information evaluation.

Lastly, relating to consumer assist, we’ve developed an AI-powered customer support bot. We feed AI with information from Footprint, which spans GameFi, NFT, DeFi, and different areas, to construct a customized AI customer support bot for Footprint. This AI bot gives quick help to customers by answering questions associated to the usage of Footprint, together with information sorts, information definitions, API utilization, and many others. This vastly will increase the effectivity of buyer assist whereas decreasing the quantity of guide work.

Nevertheless, it’s price noting that whereas AI functions can improve productiveness and assist resolve most challenges, they might not be omniscient. Primarily based on our information processing expertise, AI can help in fixing roughly 70% to 80% of challenges.

From a broader perspective, whatever the area by which AI is utilized, a essential consideration is the extent of acceptance of AI’s fault tolerance. Completely different software situations have totally different fault tolerance necessities. There’s a must steadiness the accuracy and reliability of AI towards folks’s tolerance for error.

As an illustration, in healthcare, the choice to belief both AI or a doctor could contain trust-related challenges. Within the funding house, AI can present elements that affect the course of BTC costs, however folks should have doubts when making precise purchase or promote choices.

Nevertheless, exact accuracy might not be paramount in advertising and marketing and operational analytics, similar to consumer profiling and tiering, as a result of minor errors gained’t considerably impression. Consequently, error tolerance is extra readily accepted in these contexts.

At the moment, Footprint is primarily centered on information in its efforts to combine AI with Web3, which presents its personal set of challenges:

First, the primary problem is information technology, particularly offering high-quality information for AI to realize extra environment friendly and correct information technology capabilities. This relationship between AI and information might be in comparison with the engine and gasoline of a automotive, the place AI is the engine and information is the gasoline. Irrespective of how superior the engine, a scarcity of high quality gasoline will forestall optimum efficiency.

This raises the query of the right way to generate high-quality information, for instance, the right way to shortly and mechanically generate information in areas similar to GameFi, NFTs, DeFi, and others. This consists of mechanically organizing the information connections, primarily creating a knowledge graph. Extra particularly, it entails figuring out elements such because the protocols to which contracts are related, the sorts of contracts, the suppliers, and different pertinent particulars. The principle aim of this course of is to constantly present the AI with high-quality information to enhance its effectivity and accuracy in information manufacturing, thus making a virtuous cycle.

The second problem is information privateness. Whereas Web3 is essentially dedicated to decentralization and transparency, the necessity for privateness could grow to be paramount because the business evolves. This consists of defending customers’ identities, belongings, and transaction data. This case presents a dilemma: the transparency of information on the blockchain step by step decreases, limiting the quantity of information accessible to AI. Nevertheless, this concern will likely be addressed because the business progresses, and homomorphic cryptography is a potential resolution.

In conclusion, the convergence of AI and Web3 is inherently intertwined with a core downside: information accessibility. In essence, the final word problem for AI lies in its entry to high-quality information.

I imagine attaining important integration and adoption of Web3 and AI depends upon addressing two elementary challenges. First, there’s a necessity to supply enhanced providers to Web3 builders and builders, particularly in areas similar to GameFi, NFTs, and social platforms. Second, it’s crucial to cut back the boundaries on the applying entrance to make sure a smoother consumer entry into the Web3 panorama.

Let’s begin with serving the developer neighborhood. On this space, two main sorts of functions stand out.

One class is AI-powered growth platforms. These platforms use AI know-how to automate the creation of code templates. Whether or not for constructing DEX platforms or NFT marketplaces, these platforms can intelligently generate code templates tailor-made to the precise wants of builders, considerably rising growth effectivity.

In video games, AI can velocity up the creation of sport fashions and the technology of photos, thus accelerating the sport growth and launch course of. These platforms have allowed builders to focus extra on creativity and innovation reasonably than extreme time on repetitive, primary duties.

The opposite class revolves round AI-powered information platforms. These platforms use AI to autonomously generate domain-specific information in numerous industries similar to GameFi, NFTs, SocialFi, and DeFi. The aim is to decrease the edge for builders to make use of and apply information, and simplify information evaluation and use.

By means of AI, these platforms can mechanically generate various information units, enriching builders with wealthy information assets and bettering their understanding of market tendencies, consumer conduct, and extra. By offering builders with complete information assist, these information platforms take away information utilization boundaries and catalyze ingenious functions’ emergence.

Mass adoption has all the time been a key problem within the Web3 house. For instance, the market has just lately seen the emergence of blockchain options with nearly negligible charges aimed toward rising transactions per second (TPS). As well as, options such because the MPC pockets successfully tackle the first barrier to migration from Web2 to Web3 by overcoming migration challenges.

The answer to those challenges doesn’t rely solely on AI know-how however is intertwined with the holistic evolution and growth of the Web3 ecosystem. Whereas AI performs a key function in bettering effectivity and decreasing boundaries, the underlying infrastructure and progress of Web3 stay key elements in fixing the mass adoption downside.