Kaja is a neural net trained with Ethereum blockchain data. You can ask Kaja any question about Ethereum data and get an answer. Questions can range from NFTs to DeFi protocols. Answers would often be in the most relevant format like charts or data tables.
Hello all,
I'm Priyank, co-founder and CEO of MakerDojo(https://makerdojo.io), a data analytics platform for Web3. MakerDojo helps users draw insights by enabling them to write SQL queries on blockchain data and create dashboards.
When talking to the MakerDojo users, we observed that people have many questions about blockchain data and want to get data-backed insights. But these questions often go unanswered for the following reasons:
- Most Web3 analytics products require you to have some technical knowledge (like SQL, GraphQL, etc.)
- Without it, you would need to work with the community of data scientists through bounties or public queries.
Both of the above add a high barrier to entry. After writing around 500 SQL queries on MakerDojo, we also realized that data analytics queries are often repetitive.
We built Kaja to solve the above-stated problems. Kaja is a neural net trained with Ethereum data. It can answer any analytics question on Ethereum, eliminating the need for users to have technical abilities or dependence on the community.
You can ask Kaja any question about Ethereum data, and you will get an answer. If you like the answer, you can add them to a dashboard that will keep the answer up-to-date with new data. If the answer is not what you expected, you can iterate on the question in a conversational style. If you are an advanced user, you can view the query through which Kaja answered your question and fine-tune it to your liking.
Questions can be about any crypto-related concept. Here are some example questions you can ask:
What is the volume of an NFT?
How many NFTs have been in circulation since the first mint?
What is the top liquidity pool by TVL on a specific Defi protocol?
What is the APY rate of a lending protocol?
Kaja will answer your question in the relevant format, like a chart (bar chart, area chart, pie chart), a data table, or just plain answers in the text.
We are excited about the results and are in a closed alpha stage. We are starting to invite folks to start trying it out. If you are interested, please visit https://kaja.ai to get an invite.
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