A new workflow leveraging AI tools has reportedly tripled the efficiency of on-chain analysts, streamlining the process from monitoring to decision-making. The workflow involves four key steps: data collection, AI-driven OCR and structured extraction, batch analysis, and decision-making. Data collection is achieved using platforms like Dune Analytics, Nansen, and Arkham to monitor address and protocol changes, with tools like Res-downloader for capturing blockchain browser pages. AI tools such as Grok, Claude, or Gemini are then used for OCR and structured data extraction, converting screenshots into JSON format for storage in Notion or Excel. The analysis phase involves feeding data into large models to identify patterns, potential institutional or whale activities, and rug pull risks, with cross-verification using social media sentiment peaks. Finally, AI-generated summaries are manually reviewed and recorded in personal databases, forming a historical case library. A recent case study highlighted a 180% net inflow to a meme contract, leading to a 2.8x price surge, demonstrating the workflow's potential effectiveness.