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)
This project creates domain-specific AI agents that process domain-specific uploaded documents and perform specific functions within specified contextual boundaries. Through the combination of natural language processing and domain knowledge models, the agents extract, analyze, and perform operations on information while being sensitive to field-specific requirements. The system employs a multi-layered architecture: domain parsers process documents, domain models properly comprehend content, and a secure environment executes predefined actions. Sophisticated workflows in expert domains such as legal, medical, financial, and technical domains are automated. Among the most important innovations are contextual awareness mechanisms, programmatic action pipelines without programming expertise, and validation protocols to guarantee accuracy in high-stakes contexts. Implementation outcomes suggest improved processing efficiency, reduction of human error, and improved regulatory compliance compared to traditional methods.
"AI Agents for Domain-Specific Document Processing: Task Automation in Contextual Environment ", International Journal of Science & Engineering Development Research (www.ijrti.org), ISSN:2455-2631, Vol.10, Issue 4, page no.a292-a297, April-2025, Available :http://www.ijrti.org/papers/IJRTI2504043.pdf
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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