L-01 Labs project

Hüni — KI-Gemeindeassistent

AI Municipal Assistant for Hünenberg. RAG-powered chat with verifiable sources, transparent response generation, and Swiss data sovereignty.

Concept
Hüni — KI-Gemeindeassistent — Mockup preview

Problem

Residents often spend time searching for the right information or the appropriate online service on municipal websites. Although Hünenberg already provides a modern online service portal and digital offerings such as the eZug app, information retrieval and navigation remain a key part of many citizen interactions.

Conventional AI chatbots are only partially suitable for use in the public sector. Responses may be inaccurate when the underlying data is incomplete, data processing often takes place outside Switzerland, and sources are either missing or difficult to verify. Traditional FAQ systems, on the other hand, quickly reach their limits when faced with the diversity of individual citizen inquiries.

Solution

Hüni is an AI-powered municipal assistant built on Retrieval-Augmented Generation (RAG). Its knowledge base consists exclusively of verified and publicly available municipal information sources, including regulations, official publications, online services, forms, and other relevant content.

The system is based on three core principles: traceable source references for informational responses, no handling of personal administrative cases, and consistent refusal to answer when sufficient information is unavailable. If a question cannot be answered reliably, the user is referred to the appropriate municipal office.

The architecture is designed entirely around Swiss data sovereignty. Hosting and data processing take place in Switzerland and can be operated in compliance with Swiss data protection requirements. Estimated operating costs for a municipality with approximately 9,000 residents are between CHF 200 and CHF 400 per month.

Target audience

Primary Target Groups

  • Small and medium-sized Swiss municipalities
  • Cantonal administrations focused on digital citizen services
  • Municipal offices with a high volume of recurring information requests

Secondary Target Groups

  • Municipalities with multilingual populations
  • Municipal associations and shared-service organizations
  • Providers of digital government solutions as an integrable white-label component

Tech Stack

Modello linguistico di grandi dimensioni (LLM) Retrieval-Augmented Generation (RAG) JavaScript (Vanilla) HTML5 / CSS3 Proxy API serverless Database vettoriale Hosting cloud svizzero Python (crawler della sitemap) API eZug (prevista)

Compliance

Legge federale svizzera sulla protezione dei dati (nLPD 2023) EU AI Act (allineamento Limited Risk) Infrastruttura di hosting conforme ISO 27001 WCAG 2.1 AA (prevista) eCH-0014 (previsto) BGEID (previsto) Principi OCSE sull’IA (2019) Sovranità svizzera dei dati Hosting in Svizzera

Roadmap

Q2 2026 — Pilot

Functional prototype with a curated knowledge base (≈30 entries), browser-based widget, and offline mirror. Execution of response quality and robustness testing using real-world use cases. Evaluation by interested municipal stakeholders.

Q3 2026 — Backend

Cloudflare Worker as an API proxy. Vector database (Qdrant, Swiss hosting). Sitemap crawler for automated content ingestion. Planned user and field testing with residents.

Q4 2026 — Pilot Operation

Preparation of a production-ready pilot operation in collaboration with an interested municipality. Analytics dashboard for administrative staff (frequently asked questions, escalations, usage patterns). Continuous refinement of the knowledge base.

2027 — Scaling

Assessment of transferability to additional Swiss municipalities. Full multilingual support (DE / FR / IT / EN). Evaluation of integration with existing digital identity solutions such as eZug.

References & Reading

Scientific Foundation

  • Lewis, P. et al. (2020): Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks. arXiv:2005.11401.

Data Protection & Governance

  • Swiss Federal Data Protection and Information Commissioner (FDPIC): Guidelines for the Use of Artificial Intelligence in Public Administration, 2024.
  • OECD (2023): Recommendation on Artificial Intelligence – Public Sector Application.

Swiss Digitalization Strategies

  • Swiss Federal Chancellery: Digital Administration Switzerland Strategy 2024–2027.
  • Canton of Zug: eZug – Digital Administration, strategy documents and public information.

FAQ

How does Hüni prevent hallucinations?
Hüni may only answer based on the provided knowledge base. If no official source is found, the response is standardised: "I have no official data on this. Please contact the municipal office.This rule is embedded as a core security requirement within the system design and cannot be bypassed by end users.
Are personal data processed?
Hüni is not designed to handle personal administrative matters. If personal data is entered, it is not used to provide information, and users are advised to contact the appropriate municipal office directly.
Where is the data hosted?
All data is hosted in Switzerland and falls exclusively under Swiss data protection law (revFADP). The knowledge base contains only public municipal documents — no personal data.
How current is the knowledge base?
In the pilot, the knowledge base is maintained manually. For production, a nightly sitemap crawler is planned that automatically reindexes huenenberg.ch. Static PDFs are re-ingested when versions change.
What does it cost to run?
Estimated CHF 200–400 per month for a municipality of 9,000 residents at moderate usage (~3,000 queries per month). Main cost items: Anthropic API calls, vector DB hosting, Cloudflare plan.
Can other municipalities adopt Hüni?
Yes. The architecture is municipality-neutral. Adapting it for a second municipality typically takes one to two weeks: swap knowledge base, adjust branding, reconfigure system prompt.
What happens with legally binding queries?
Hüni explicitly does not provide legally binding information and consistently refers to the municipal office whenever such a query is suspected. This restriction is transparently communicated in the disclaimer and anchored in the system prompt.
Which language model is used?
Claude Sonnet 4 from Anthropic, chosen for its excellent Swiss-German and Standard-German capabilities as well as EU hosting. The system is model-agnostic — switching to Mistral, Aleph Alpha or other European providers is prepared.
Case Study

Case Study

How could a Swiss municipality with approximately 9,000 residents use an AI assistant to provide citizen services around the clock while ensuring data protection, transparency, and verifiable information sources?

Background

Hünenberg already offers an advanced portfolio of digital services, including an online service portal, eZug integration, and an active strategy for digital development. The next stage of evolution is to explore how AI-powered systems can enhance citizen services without compromising data protection, transparency, or data sovereignty.

The Hypothesis

A curated RAG-based assistant, powered exclusively by official municipal information sources, could reliably answer common citizen inquiries while directing more complex requests to the appropriate administrative offices.

The Prototype

For this concept study, a functional demonstrator was developed featuring a curated knowledge base, a browser-based widget, and extensive response-quality testing. Particular emphasis was placed on answer traceability, source verification, and the controlled handling of questions that fall outside the available knowledge base.

The Path to a Pilot Deployment

The architecture is designed as a modular system. An automated sitemap crawler will maintain the knowledge base, an API proxy addresses security requirements, and a Swiss-hosted vector database ensures data sovereignty and privacy. Estimated operating costs for a municipality of approximately 9,000 residents range from CHF 200 to CHF 400 per month.

The key difference compared to generic AI chatbots: responses are based exclusively on verified sources. Information that is not supported by the knowledge base is not answered but instead referred to the appropriate authority.

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What should we build together?

This project is part of our lab research. If you need something similar — your own AI tool, dashboard, custom workflow — talk to us. Every engagement starts with an honest assessment, not a sales pitch.