Jul 2026· International Conference Computing Methodologies and Communication· pp. 1732-1738· 0 citations· 17 references
Abstract
Organizations today rely on multiple diversified digital platforms and tools for task planning, daily schedule aggregation, human resource support, communication, document handling, etc. These tools often operate independently, expecting employees to switch between multiple apps, leading to excessive cognitive load, reduced productivity, and unnecessary chaos. This paper introduces Collabrium, an AI-enabled enterprise collaboration platform that unifies HR assistance, daily agenda aggregation and management, In-chat reminder, Business Language translator, Contextual Tagging, Multi-Message Abstraction, and Document-based question answering features. These features make Collabrium a unique and unified platform for improving productivity and workflow management. The system incorporates semantic text understanding, retrieval-augmented generation, and vector-based similarity search to convert conversations into vectors and fetch contextually similar vectors within a vector database. The proposed approach improves functional effectiveness by incorporating artificial intelligence directly into communication workflows and tasks, for better workflow operation.
A single, general-purpose AI workflow automation platform built around n8n, using n8n – a visual workflow automation engine – as the layer that actually thinks, decides, and adapts, while a conventional web application supplies the interface and storage around it.
Sanketh B M, T. Vasudev, Karthik R· International Journal of Res...· 0 citations
A taxonomy of five AI paradigms (perceptive, dialogic, interpretive, structural and contextual), each defined by its contribution to one of three knowledge processes and by the type of work it serves is proposed, with a boundary marked where collective tacit knowledge resists codification.
Mohamed Amine Guedria, Maximilian Dommermuth· European Conference on Knowl...· 0 citations
The rapid advancement of LLMs has opened new opportunities in automated software engineering, driving progress in code understanding, agent-based workflows, and productivity tools. However, existing code intelligence systems have largely sidelined the end-users they aim to serve—the developers themselves. Developers ex...
Yuhong Liu, Yu Su, Zhipeng Peng et al.· SIGSOFT FSE Companion· 1 citation
This workshop aims to bring together researchers and practitioners to examine how enterprise AI agents can successfully move from prototypes to production, and focuses on three pillars: 1) Agent architectures and systems; 2) Enterprise applications and deployments; 3) Evaluation and governance.
Min Du, Anbang Xu, Jasmine Jaksic et al.· Proceedings of the 32nd ACM...· 0 citations
It is argued that organizations capturing durable value are not necessarily those with the most advanced models, but those that have redesigned decision workflows, built human-in-the-loop verification into high-stakes processes, and treated GenAI as a collaborator rather than an oracle.
Naresh Sharma, Rohit Kumar, Himanshu Verma et al.· Journal of Intelligent Decis...· 0 citations
Experiments on public benchmarks and real-world industrial BI workloads show that QwenPaw-Data improves both verifiable data access capability and higher-level analytical quality, offering a practical foundation for reliable, traceable, and continuously improving enterprise data agents.
