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.
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| Original publisher | arXiv cs.AI |
| Canonical URL | https://arxiv.org/abs/2605.22825 |
| Publication time | Mon, 25 May 2026 00:00:00 -0400 |
| Retrieval time | 2026-05-25T04:07:35.648Z |
| Last seen | 2026-05-25T04:07:35.648Z |
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Basis: Derived from the published RSS/Atom feed. Contact: [email protected]. Reviewed: 2026-07-24.
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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.
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