KPI2KVI: A Multi Agent Workflow for Calculating Key Value Indicators from Service Descriptions
The paper introduces KPI2KVI, a tool designed to compute Key Value Indicators (KVIs) from service descriptions. It utilizes a multi-agent workflow powered by Large Language Models to automate the extraction and calculation of KVIs. The tool aims to improve the consistency and transparency of KVI calculations, facilitating better decision-making for stakeholders.
- ▪KPI2KVI transforms natural language service descriptions into computed KVI estimates.
- ▪The tool orchestrates a deterministic multi-agent workflow that elicits missing service context and generates service-specific KPIs.
- ▪Simulations demonstrate that KPI2KVI produces complete mappings from service descriptions to KVI intervals.
Opening excerpt (first ~120 words) tap to expand
Computer Science > Distributed, Parallel, and Cluster Computing arXiv:2605.22825 (cs) [Submitted on 31 Mar 2026] Title:KPI2KVI: A Multi Agent Workflow for Calculating Key Value Indicators from Service Descriptions Authors:Masoud Shokrnezhad, Tarik Taleb, Yan Chen, Qize Guo View a PDF of the paper titled KPI2KVI: A Multi Agent Workflow for Calculating Key Value Indicators from Service Descriptions, by Masoud Shokrnezhad and 3 other authors View PDF HTML (experimental) Abstract:Key Value Indicators (KVIs) provide a decision oriented view of a service by summarizing how operational performance translates into stakeholder value, risk, and outcomes.
…
Excerpt limited to ~120 words for fair-use compliance. The full article is at arXiv cs.AI.