We give researchers the data they need by providing them to access high quality curated datatsets of on-chain data.

Current Status

We are currently building our MVP. Pulling data from our first API, we have built our database, and are reviewing the data we have pulled to determine its usefulness and accuracy.

We will begin to build the automated agent that serves to construct our curated datasets and update them automatically every 30 days for Ocean Marketplace.

We will sell our datasets on Ocean Marketplace for very low prices. Once the PoC has been validated, we will apply for a grant via Ocean Protocol Shipyard. With additional funds, alongside tapping into more API's and building more curated datasets, we will build an AI Model that will allow subscribers to query the datatsets and derive insight from them. (see #3 in Growth Strategies below)

Target Audience:

Data scientists (specifically web3 for MVP)

AI Builders

Token Engineers

The Problem(s):

Existing on-chain data providers offer data through APIs:

Disadvantages:

• Require technical expertise to use (can be a barrier for others that lack technical expertise)
• Data is often raw and unfiltered
• Time-consuming to extract meaningful insights (This can involve cleaning the data, dealing with missing or inconsistent data, aggregating data, calculating metrics, and so on. ) Can be a barrier for those that lack time

DataBites Benefits:

1. DataBites provides curated datasets, saving users the time and effort of data extraction and cleaning.
2. Our datasets are tailored to the needs of our users, providing them with the specific data they need for their analysis or research.
3. Our datasets are easier to use for non-technical users, enabling the growing trend of AI + Humans to speed past learning curves such as those involved with analyzing data sets

DataBites MVP Features:

• Downloadable Curated Datasets

Team

Daniel Haboush a.k.a. Curious Rabbit - CEO of Lucky Rabbit Tenders, a Token Engineering Firm

Kirk T Schroder - Chief Legal Officer of Lucky Rabbit Tenders

ARLab - Dev Shop

ENS Address:

Databites.eth - 0x80B1b27E94DDbd687F5200Dd48c408d7e5f53740

Market Analysis

Data Preparation Market:

• Projected CAGR of 22.5% over the next five years.
• Rising demand due to digital disruption and the need for faster debugging time.
• Analytics requirement, particularly data analytics, becoming pervasive among organizations.
• Significant demand for data preparation services to address rising data complexities. (source)

AI Market:

• Expected CAGR of 36.8%.
• Market size projected to reach USD 1,345 billion by 2030. (source)

Data Science Platform Market:

• Forecasted CAGR of 27.7%.
• Market size projected to reach USD 322.9 billion by 2026. (source)

Blockchain Technology Market:

• Anticipated CAGR of 87.7%.
• Market size valued at USD 10.02 billion in 2022.
• Continuous growth expected from 2023 to 2030. (source)

Data Scientists Employment:

• Projected CAGR of 36% from 2021 to 2031.
• About 13,500 annual job openings on average.
• Rapidly growing demand for data scientists across industries. (source)

Competition

Our indirect competitors are existing on-chain data providers that offer data through APIs such as Glassnode, Santiment, Messari, Nansen, Dune, Flipside Crypto, CoinMarketCap, CoinGecko, NFT Scan, CryptoSlam, DefiLLama, Token Terminal, Gecko Terminals, and DappLooker.

A direct competitor is Flipside Data Shares, they sell curated datasets on snowflake marketplace.

Growth Strategies

1. Grow Database & Datasets→ Expansion into Other Data Types & APIs:
   • Sign up to and pull from more Web3 on-chain data APIs
   • Expand in to off chain datasets and data from other complimentary industries
   • Specialize Datasets further for Target Audience (data scientists, ML models etc)
2. Build Website & Dapp:
   • Create a nice website for users
   • Utilize the infrastructure and tools provided by Ocean Protocol to create our own data marketplace/Dapp
3. Train our own AI Model
   • Develop and train our own AI models using the curated datasets we have created (ex: web3 market research)
   • Give a language model access to our data (semantic indexing, RAG retrieval augmented generation)
4. Education-Focused Datasets:
   • Develop datasets with a specific focus on education, catering to the needs of people who want to learn to use the AI to gain insights from Data
5. Token Gated Community:
   • Create a Token Gated community for users who have out Data tokens
   • Soulbound tokens given to those who buy our datasets

Marketing

Outreach:

Twitter, LinkedIn,

Community Discords

No website for MVP

Community & Partnership Focused:

We will seek to form alliances with blockchain and cryptocurrency communities, as well as data science and AI communities, as a means to promote our curated datasets and build our reputation.

Non-exhuastive list of potential comunities:

• Ocean Protocol
• Open Data Community
• Gitcoin
• Token Engineering Academy
• Token Engineering Commons
• Metrics DAO
• Web3 Academy