Investigation of whether Retrieval-Augmented Generation embedded in an agentic workflow can mitigate limitations and produce accurate and traceable schema and protocol mappings with minimal human intervention and produces accurate and auditable outputs where the model alone falls short.
Enterprise data pipelines have grown in scale and interdependency faster than the operational practices used to maintain them. Pipeline failures are still predominantly diagnosed and remediated by human engineers reading logs, tracing lineage, and applying tacit knowledge, which produces long mean-time-to-recovery and...
A. Kolla, Ameya Kokate· International Journal of Fro...· 0 citations
This paper examines Data Agents from a harness-centric perspective, introducing a taxonomy of Data Agents and associated data environments, and identifying four open reliability problems: inactive semantic calibration, missing clarification, missing experience transfer, and the missing verification-repair repository.
Hua-Chi Zhou, Yu-Jing Zhang, Jia-He Du et al.· 0 citations
Cross-model evaluation across four LLM backends and human expert validation confirm architectural generalizability and evaluator reliability and an ablation study confirms that the Data Analysis and Report Aggregation agents are the primary drivers of output quality.
M. ManojN, S. Vijayakrishna, Manjunath Srinivas et al.· 0 citations
Raven is introduced, an open-source multi-agent ecosystem that automatically constructs and evolves modular harnesses for specific models and domains, treating each executable model--harness pair as a composable unit of intelligence.
This work systematically study AI products with demonstrated adoption, together with their product workflows and users, to identify real-world tasks for which AI has established practical demand across diverse professional domains and establishes StartupBench as an empirical measure of progress toward E2E completions o...
CascadeAgent is introduced, a multi-agent framework that automates prompt adaptation and specialization through error-driven semantic refinement and discusses the evaluation and deployment lessons from this setting, including precision– coverage trade-offs, negative labels for abstention, semantic verification of ambig...
Peng Gao, Athanasios N. Nikolakopoulos, Zhuo Cheng et al.· 1 citation
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