# AgentSLA : Towards a Service Level Agreement for AI Agents

arXiv: https://arxiv.org/abs/2511.02885 · HTML: https://mlsanity.com/paper/2511.02885/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 14 of its 44 references that are in the map.
- First posted on arXiv 4 Nov 2025.

## Builds on (most cited first, 14 of 14)

- [A Unified Approach to Interpreting Model Predictions](https://mlsanity.com/paper/1705.07874/) (2017)
- ["Why Should I Trust You?": Explaining the Predictions of Any Classifier](https://mlsanity.com/paper/1602.04938/) (2016)
- [Model Cards for Model Reporting](https://mlsanity.com/paper/1810.03993/) (2018)
- [Measuring Neural Net Robustness with Constraints](https://mlsanity.com/paper/1605.07262/) (2016)
- [Croissant: A Metadata Format for ML-Ready Datasets](https://mlsanity.com/paper/2403.19546/) (2024)
- [A Systematic Review of Green AI](https://mlsanity.com/paper/2301.11047/) (2023)
- [Model-as-a-Service (MaaS): A Survey](https://mlsanity.com/paper/2311.05804/) (2023)
- [Quality Assurance for AI-based Systems: Overview and Challenges](https://mlsanity.com/paper/2102.05351/) (2021)
- [A domain-specific language for describing machine learning datasets](https://mlsanity.com/paper/2207.02848/) (2022)
- [Measuring AI agent autonomy: Towards a scalable approach with code inspection](https://mlsanity.com/paper/2502.15212/) (2025)
- [Adapting SQuaRE for Quality Assessment of Artificial Intelligence Systems](https://mlsanity.com/paper/1908.02134/) (2019)
- [Building BESSER: an open-source low-code platform](https://mlsanity.com/paper/2405.13620/) (2024)
- [Service Level Agreements and Security SLA: A Comprehensive Survey](https://mlsanity.com/paper/2405.00009/) (2024)
- [Towards Sustainability Model Cards](https://mlsanity.com/paper/2507.19559/) (2025)

## Built on by (most cited first, 1 of 1)

- [LEGIT: Credentialing Protocol for Trustworthy AI Agent Marketplaces](https://mlsanity.com/paper/2609.21325/) (2026)

## Abstract (arXiv)

AI components are increasingly becoming a key element of all types of software systems to enhance their functionality. These AI components are often implemented as AI Agents, offering more autonomy than a plain integration of Large Language Models (LLMs), moving from a Model-as-a-Service paradigm to an Agent-as-a-Service one, bringing new challenges to the development of smart software systems. Indeed, while support for the design, implementation, and deployment of those agents exist, the specification of Quality of Service (QoS) and definition of Service Level Agreements (SLAs) aspects for those agents, important to ensure the quality of the resulting systems, remains an open challenge. Part of this is due to the difficulty to clearly define quality in the context of AI components, resulting in a lack of consensus on how to best approach Quality Assurance (QA) for these types of systems. To address this challenge, this paper proposes both a quality model for AI agents based on the ISO/IEC 25010 standard, and a domain specific language to support the definition of SLAs for the services provided by these AI agents.