👀Overview
web3analyzer leverages a multi-step, automated process to collect, analyze, and merge data from various sources. The system integrates several external applications to ensure robust performance and data accuracy:
Google.com: Utilized for file generation and secure storage.
Make.com: Orchestrates the entire automation workflow.
Apify.com: Extracts data from websites and white papers.
PDF.co: Reads and processes PDF files.
OpenAI / ChatGPT: Powers the analytical engine that evaluates and scores project data.
The process is executed in eleven AI API calls, with each stage building upon the previous one. The final outcome is a merged project report that consolidates all relevant information into a structured format.
☝ TO CONSIDER!
Do you know the term 💩in -> 💩out?
Access to data is crucial for automation. If data is missing from a website or whitepaper, the output quality may decline. In challenging cases, difficulties often arise due to the structure of the website or whitepaper.
Extracting data from nested information, graphics, or graphs can be challenging. Similarly, complexities arise with unusual link structures, multiple redirects, or language-specific implementations, such as /en, /fr, or /de.
The automation can therefor also help the projects' owner.
Is the website structure clean?
Is the information easy to find?
Are there any unnecessary redirects?
Is the information only in graphics or graphs?
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