Pérez-Leis, NicolásLacalle, DavidCastro-Castro, Paula-María2026-09-172026-09-172025Pérez-Leis, N., Lacalle, D., & Castro-Castro, P. M. (2026). Study on the Implementation of AI Inference Services in a Business Environment. In Proceedings XoveTIC 2025: Impulsando el talento científico (pp. 177-184). Servizo de Publicacións UDC. https://doi.org/10.17979/spu.23.c33978-84-9749-925-5https://hdl.handle.net/2183/49298Presentado en: VIII Congreso Xove TIC: impulsando el talento científico. Octubre, 2025, A Coruña.[Abstract] Diffusion-based generative models, such as Stable Diffusion, have revolutionized the generation of images from textual descriptions. However, their high computational cost represents an obstacle in production environments. This work analyzes strategies for their efficient and reproducible deployment in scalable clusters, with the technical support and resources provided by the company. The study is conducted in a real corporate context, where these models are already being used to accelerate design processes and optimize key stages of the value chain. To achieve this, different inference service strategies are compared in terms of latency, GPU utilization, and integration capabilities.engAttribution-NonCommercial-NoDerivatives 4.0 Internationalhttp://creativecommons.org/licenses/by-nc-nd/4.0/Artificial IntelligenceDiffusion modelsStable diffusionInference servicesGPU utilizationconference outputopen access10.17979/spu.23.c33