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Driving Innovation with Speech-based Conversational AI

LBBW is calling on AI experts to develop a proof of concept showcasing that speech-based conversational AI can enhance verbal communication in complex B2B environments. Starting with real estate financing, help us explore how AI-driven spoken dialogue systems can streamline decision-making and stakeholder interactions. Successful participants will gain access to co-creation opportunities, research collaborations, or long-term partnerships with LBBW. 

Who can take part 
Open to researchers, AI specialists, startups, tech companies and all other innovators who are focused on NLP, LLMs, conversational AI, or the digital transformation of financial services. 

  • 🏆  Rewards
    Business Partnership, Research Collaboration and Career opportunities
  • 🕑  Deadline
    Feb 4, 2025, 10:59:00 PM
  • 🇪🇺 Scope

    European Union

  • ❓Questions

    Feel free to join our Q&A Calls

  • 👥 Looking for a team?
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Real estate financing 

Description 

International real estate financing involves complex, multi-stakeholder interactions where efficient communication between banks, developers, and investors is critical. The primary goal is to optimize spoken communication, allowing for more effective, real-time dialogue in high-stakes environments. This could be achieved by either providing real-time insights and recommendations to advisors during conversations or by directly enabling intelligent, dynamic dialogues with stakeholders in real-time

Exemplary scenarios 

The following scenarios highlight potential applications of LLMs in real estate financing that you can use for orientation & understanding: 

1. Initial Consultation: 
  • A real estate developer seeks financing for a new construction project and initiates a conversation with the bank. 
  • The bank advisor gathers key information about the project (location, project type, estimated investment). 
  • The LLM assists by analyzing the developer's input and identifying missing data, prompting the advisor or suggesting follow-up questions. 
  • In the best-case scenario, the conversation is entirely supported by the LLM, ensuring smooth data collection without requiring additional personnel. 
2. Financing Options and Negotiation: 
  • The bank advisor presents various financing options based on the project’s requirements and the developer's financial situation. 
  • The developer raises questions regarding interest rates, repayment schedules, or potential incentives, with the LLM providing real-time suggestions and clarifications. 
  • The LLM adapts financing options based on the developer's preferences, allowing the advisor to explain the implications of any changes effectively. 

Criteria 

  • Multilingual and Cultural Adaptation: The model should support conversations in multiple languages and consider regional nuances. Note: The first language the model should support is English, with the possibility of expanding to other languages in future phases. 
  • Financial Context Understanding: The model must be capable of understanding financial terminology and global real estate financing processes to offer accurate insights. Note: The very specific financial domain knowledge might be developed later on in a co-creation process, allowing you to focus more on the linguistic and conversational aspects in the initial phase. 
  • Interactive and Targeted Support: The LLM should facilitate both advisor support and direct communication, tailoring responses to meet the specific needs of the project developers and investors. 
  • Real-time Interaction: The model must operate in real-time, providing timely recommendations and processing feedback during live conversations. 

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