Revolutionizing Construction with AI: Automated Task Extraction from LINE Messages
Analysis
This article details a fascinating application of Generative AI to automate task extraction from LINE messages within a construction company. It showcases the practical application of AI in streamlining communication and improving efficiency by intelligently processing a large volume of daily messages. The project highlights innovative techniques to overcome challenges like message fragmentation and noise to ensure reliable and accurate information processing.
Key Takeaways
- •The project uses a multi-stage process involving LINE Messaging API, Vercel, Supabase, n8n, and Gemini API for task extraction.
- •The system incorporates a 60-second buffer to handle fragmented messages, combining them for better classification.
- •A staging table ('line_task_queue') is used to manage and validate AI outputs before integrating them into the ERP system.
Reference / Citation
View Original"I'm building the business system for a construction company by myself. There are 14 employees and over 20 LINE groups. 200-400 messages are exchanged every day."