Integreat Chat: A Privacy-First RAG Conversational System for Immigration Consultation

Integreat Chat is an open-source project that combines self-hosted large language models (LLMs) with vector databases to provide intelligent Q&A services for immigration consultation. Its core feature is privacy-first—all data processing is done locally, avoiding third-party LLM services from accessing users' sensitive information. The project aims to address the challenges of privacy protection and multilingual services in immigration consultation, supporting self-hosted deployment to adapt to the needs of different institutions.

With the popularization of digital services, immigration consultation faces two major challenges: providing accurate information to multilingual and cross-cultural groups, while protecting privacy data from abuse. The Integreat Chat project was developed by the DigitalFabrik team, with the goal of building a fully self-hosted conversational system that integrates LLMs and Retrieval-Augmented Generation (RAG) technology to provide intelligent consultation for Integreat App users. All data processing is done locally to ensure sensitive information does not flow to external service providers.

Integreat Chat adopts a modular architecture, with core components including:

1. Self-hosted LLM Integration: A flexible interface supports multiple open-source LLMs, allowing institutions to choose models based on their hardware and needs;
2. Vector Database Support: Converts immigration policy documents, FAQs, and multilingual resources into vector embeddings for storage, enabling fast semantic retrieval to provide context;
3. Django Backend: Built on the Django framework, it has mature security mechanisms and a rich ecosystem, simplifying deployment without the need for traditional relational databases;
4. Zammad Ticket Integration: Complex consultations can be seamlessly transferred to the manual ticket system, forming a closed loop of human-machine collaboration.

The project is currently addressing the following challenges:

1. Low-Resource Language Support: Enhancing the understanding and generation capabilities for non-mainstream languages through multilingual model fine-tuning and cross-language transfer learning;
2. Mixed Code Processing: Accurately identifying and handling the common multilingual mixing phenomenon in immigrant communities (e.g., alternating between German and Arabic);
3. Language Detection and Automatic Translation: Real-time detection of user input language to ensure the accuracy of professional terms in the translation module.

Integreat Chat adopts a self-hosted architecture. User consultation content, personal information, and other data do not leave the local server, providing security guarantees for institutions handling sensitive immigration information. This design gives institutions autonomy: independently deciding the model update rhythm, controlling data storage locations, and flexibly adjusting the system to meet compliance requirements (such as GDPR), which is particularly important for European institutions.

Integreat Chat is part of the Integreat ecosystem, collaborating with the Integreat App (immigration information platform) and CMS (content management system) to form a complete chain from content production to service delivery. Currently, the code is maintained independently for easy iteration. The long-term goal is to deeply integrate with the CMS, allowing immigration service institutions to deploy intelligent consultation conveniently. As an open-source project, it welcomes community contributions and is expected to become a benchmark for the digital transformation of immigration services in the future, proving that privacy protection and AI intelligence can achieve a win-win situation.