QT-GenAI for Local Gov
2025-05-07 22:26:22

QT-GenAI Enhances Local Government with Secure AI Solutions

QT-GenAI Enhances Local Government Operations Through Secure AI Solutions



In a landmark collaboration, And-Dot, a Tokyo-based enterprise providing generative AI solutions, has partnered with QTnet, a telecommunications company within the Kyushu Electric Power Group, to launch the corporate generative AI platform, QT-GenAI. This innovative platform has recently achieved compatibility with LGWAN (Local Government Wide Area Network), enabling a private secure connection specifically tailored for local government entities.

With the rise of municipalities leveraging this groundbreaking feature, local governments are beginning to utilize generative AI while ensuring robust security measures. Notably, some local governments have already reported positive outcomes from implementing QT-GenAI into their internal networks. This connection to LGWAN paves the way for municipal staff to safely engage with generative AI tools without concerns for external breaches.

Ensuring High-Level Security and Efficiency for Local Governments



LGWAN is designed to interconnect the internal network (LAN) of various public agencies, creating a closed network that is detached from the internet. This secure framework forms the backbone for heightened safety across governmental operations. By integrating QT-GenAI with LGWAN, municipal employees can effectively employ generative AI, enjoying both security and efficiency.

QT-GenAI stands out for its user-friendly interface that allows even those with minimal technical knowledge to harness the power of generative AI. As a result, local governments can expect significant improvements in document preparation, inquiry handling, and various administrative tasks. An impressive highlight is the case study from Fukuoka City, where municipalities utilizing QT-GenAI have experienced an average 33% reduction in operational workloads through practical applications.

Features of QT-GenAI



QT-GenAI, a collaborative effort between And-Dot and QTnet, presents multifaceted generative AI capabilities specifically for enterprise use. Its foundation rests upon a Large Language Model (LLM), which leverages advanced natural language processing capabilities to cater to a diverse range of needs from businesses and local entities, ensuring both security and scalability.

Key Features:


  • - Support for Multiple AI Models: QT-GenAI accommodates leading generative AI models like GPT, Gemini, and Claude, allowing users to select the most suitable model for their specific use case.
  • - Multimodal Input Handling: This platform supports not just text inputs but also images, PDFs, videos, and audio, enabling comprehensive information processing across various formats.
  • - High-Security Environment: It includes features for constructing enterprise-level usage environments, access restrictions, filtering capabilities, and log management, assuring confidentiality even with sensitive operations.
  • - Intuitive User Experience: Designed with prompt-based functionality (mode features) and compatibility across multiple devices, QT-GenAI is accessible for users without advanced insights into AI technology.
  • - Comprehensive Support: The platform offers extensive support from implementation to operational phases, including guideline development and training to facilitate the integration of the solution into business practices.

Overall, QT-GenAI represents a significant advancement in equipping local governments with the tools necessary to adapt to the modern digital age while enhancing overall operational efficiency. As the platform continues to evolve, its adoption will likely usher in a new era of AI-assisted public service, aligning technology with the growing demands of public sector administration.


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For further insights, please refer to the press releases regarding the launch and updates of QT-GenAI available on the relevant media platforms.

For more information about the companies involved:


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Topics Consumer Technology)

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