Implementation of the Digital Assistant for the Hellenic Cadaster
- The client
Hellenic Cadaster
The Hellenic Cadaster, under the jurisdiction of the Ministry of Digital Governance, is a critical national agency responsible for maintaining property records and land ownership information across Greece. The organization manages a wealth of data related to property titles, land boundaries, and cadastral surveys, providing essential services to citizens, legal professionals, and government bodies. The Hellenic Cadaster initiated a transformative project to modernize public service access, enhancing user experience through the adoption of cutting-edge Generative AI technologies.
The Hellenic Cadaster, under the jurisdiction of the Ministry of Digital Governance, is a critical national agency responsible for maintaining property records and land ownership information across Greece. The organization manages a wealth of data related to property titles, land boundaries, and cadastral surveys, providing essential services to citizens, legal professionals, and government bodies. The Hellenic Cadaster initiated a transformative project to modernize public service access, enhancing user experience through the adoption of cutting-edge Generative AI technologies.
- The case
The Hellenic Cadaster, in collaboration with UBITECH AiLabs, embarked on an innovative project to develop a Digital Assistant powered by Generative AI and Large Language Model (LLM) technologies. The primary objective was to streamline access to cadastral information and services, enabling citizens, legal experts, and businesses to interact seamlessly with the Cadaster's extensive data repository.
Prior to this project, accessing cadastral information required manual searches or in-person visits, often leading to delays and inefficiencies. Recognizing the potential of AI to transform public service delivery, the Ministry aimed to create an intelligent, user-friendly, and scalable solution capable of responding to a wide array of queries related to land and property records.
Key Objectives:
Prior to this project, accessing cadastral information required manual searches or in-person visits, often leading to delays and inefficiencies. Recognizing the potential of AI to transform public service delivery, the Ministry aimed to create an intelligent, user-friendly, and scalable solution capable of responding to a wide array of queries related to land and property records.
Key Objectives:
- Enhanced Service Accessibility:
Enable 24/7 access to cadastral information, eliminating the need for in-person visits and reducing service wait times. - Improved User Experience:
Provide a conversational AI interface capable of understanding natural language queries in Greek, catering to both casual users and industry professionals. - Operational Efficiency:
Reduce the workload on Cadaster employees by automating responses to routine inquiries, allowing staff to focus on complex cases. - Data-Driven Decision Support:
Utilize the AI's capability to analyze and respond based on vast amounts of data, offering precise information quickly.
- The challenges
The implementation of the Digital Assistant for the Hellenic Cadaster faced several significant challenges, primarily related to language complexity, data integration, privacy, and user adoption:
- Role-based Personalized Responses:
Responses based on user roles, a testament to UBITECH AiLabs’ cutting-edge fuzzy and neural search knowledge base optimization techniques. Whether you are an individual, engineer, lawyer, notary, or judicial executor, the chatbot tailors its answers to your specific needs. This level of personalization ensures that users receive tailored, role-specific information, enhancing the usability and relevance of the interactions. - Multimedia Knowledge Base:
The digital assistant incorporates an innovative feature of retrieving and presenting multimedia content, such as images, within the conversation. This visual element provides a more engaging and informative user experience, allowing users to visualize the information they seek. - Language Localization and Understanding Greek:
The LLM needed to be adapted to handle the intricacies of the Greek language, including dialects, specialized legal terminology, and unique syntactical structures related to cadastral services. Ensuring accurate comprehension and response required extensive training of the model using domain-specific datasets in Greek. - Ensuring LLM Safety and Prompt Robustness:
The generative capabilities of the LLM posed a risk of potentially inappropriate or misleading responses. UBITECH AiLabs focused on designing strong prompt structures and integrating safety mechanisms to prevent malicious use or manipulation of the chatbot, ensuring it consistently delivered reliable and accurate answers.
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