Scholarly open access journals, Peer-reviewed, and Refereed Journals, Impact factor 8.14 (Calculate by google scholar and Semantic Scholar | AI-Powered Research Tool) , Multidisciplinary, Monthly, Indexing in all major database & Metadata, Citation Generator, Digital Object Identifier(DOI)
In today’s digital environment, emails remain the primary means for professionals and corporations to communicate with one another. Nonetheless, emails contain several embedded actions which are stated in an unstructured manner using natural language, thereby necessitating manual decoding, sorting, and execution. Such actions lead to inefficiency and cognitive overload. In this article, we propose a cognitively-based multi-staged autonomous email agent which employs the power of Large Language Models (LLMs) to transform unstructured emails into actionable intelligence through structuring them. In the proposed method, there are two stages involved in the transformation process. The first stage involves a task extraction algorithm which extracts actionable items from emails while the latter stage involves a task refinement algorithm where the extracted tasks are prioritized, timed and next steps are identified.
Keywords:
Cognitive Agents, Email Automation, Large Language Models, Task Extraction, NLP, Workflow Automation, Generative AI
Cite Article:
"A Cognitive Multi-Stage Autonomous Email Agent for Context-Aware Task Extraction and Priority-Oriented Action Structuring using Large Language Models", International Journal for Research Trends and Innovation (www.ijrti.org), ISSN:2456-3315, Vol.11, Issue 4, page no.b255-b266, April-2026, Available :http://www.ijrti.org/papers/IJRTI2604172.pdf
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ISSN:
2456-3315 | IMPACT FACTOR: 8.14 Calculated By Google Scholar| ESTD YEAR: 2016
An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 8.14 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator