DeepResearch is designed with a special emphasis on supporting professional research scenarios, and its typical applications in the academic field include automatic generation of literature reviews, research hotspot tracking and interdisciplinary knowledge graph construction. Test data shows that when using the tool to conduct 'Recent Advances in Computational Biology' research, the system can complete the manual workload of a traditional team for 3 days in 2 hours. In the business analysis scenario, its competitor monitoring function can automatically capture financial report data, product updates and media reports to generate multi-dimensional competitive landscape analysis.
A prominent advantage is the system's domain adaptive capability. when dealing with specialized domains such as healthcare, the research accuracy can be increased by 40% by configuring a thesaurus of specialized terms and prioritizing crawling of authoritative databases (e.g., PubMed). when marketers use DeepResearch to conduct consumer insight analysis, the system is able to automatically identify the sentiment tendency of social media and build a correlation model with the sales data. sales data to build correlation models. The optimization of these professional scenarios makes DeepResearch go beyond the limitations of a general-purpose research tool and become an intelligent assistant for vertical domain experts.
This answer comes from the articleDeepResearch: a fully open source AI assistant for automated deep researchThe
