A Sovereign Conversational Assistant Powered by ALIA and Mistral for the AI Act Age: Architecture, Governance, and Evaluation

Alejandro Carmona-Martínez, Antonio J. Jara, Alicia Asín

Digital Twins and Living Labs are increasingly used to support conservation, safety, accessibility, and visitor experience in cultural-heritage sites. Their practical value, however, depends on interfaces that can explain heterogeneous evidence, expose provenance, and operate under public-sector governance constraints. This paper presents a Sovereign Conversational Assistant (SCA) for the Libelium Heritage Living Lab, implemented as a small-language-model (SLM) and retrieval-augmented generation (RAG) stack that combines curated heritage and operational knowledge bases with provenance logging, refusal controls, and language enforcement. We first compare the Spanish public model BSC-LT/ALIA-40b-instruct-2601 with mistralai/Mistral-Small-3.2-24B-Instruct-2506 using 19 canonical test conditions executed over 155 repeated runs across five categories: historical queries, client experience, data analysis, hallucination resistance, and safety/ethics. Mistral passed all repeated runs, whereas ALIA passed 129/155 runs, showing strong factual and visitor-information behaviour but weaker numerical analysis, cross-lingual safety, and Spanish-language enforcement. To address external validity, we add a non-sovereign baseline comparison over the 13 canonical prompts against claude-opus-4-7, gemini-3.5-flash, and gpt-5.5 under the same RAG-conditioned harness. In this prompt-level comparison, mean final scores were ALIA 0.963, Claude Opus 4.7 0.938, Gemini 3.5 Flash 0.892, GPT-5.5 0.877, and Mistral 0.871; no pairwise difference was significant after Holm correction, and ALIA was non-inferior to the best external baseline at margins of 0.05 and 0.10, whereas Mistral was not. The contribution is therefore not a new RAG algorithm, but an operational method for deploying and evaluating a governance-aware, sovereign assistant for cultural-heritage Digital Twins, together with evidence that sovereign models can be competitive in controlled heritage RAG tasks while still requiring larger, human-calibrated benchmarks before stronger claims are made.