DeepSieve demonstrates outstanding value in enterprise data analysis scenarios, and is able to handle cross-dimensional queries such as "hot products with high satisfaction in 2023". The system first decomposes sales data (structured CSV) and customer evaluation (unstructured JSON logs) into two sub-problems, calls database queries and NLP sentiment analysis tools through routing, and ultimately generates a report by integrating time, sales, and rating indicators. Tests show that its response time for handling mixed data sources is 3.7 times faster than traditional ETL processes, and it does not require pre-data integration, which meets the privacy protection needs of the financial/medical industry.
This answer comes from the articleDeepSieve: a RAG Intelligent Information Screening Tool for Processing Complex Query SourcesThe
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