AI Solutions Use Cases

AURELA

AURELA
AI research project for the autonomous understanding of regulatory requirements

CURE AudienceLens:
Audience Intelligence with Digital Audience Twins

AURELA
Autonomous Understanding of Regulation for Legal Assurance

Industry

Administration, Banking, Finance, Compliance

Background

In recent years, legislature has emerged as a primary tool for influencing world affairs. Leading nations and states associations are using their economic leverage to support their political agendas, for instance by introducing new data privacy standards for citizens of the European Union.

Although being designed to improve their respective domain of application, such legislation can have disruptive consequences for industries when they demand the modification of existing workflows and business procedures. Moreover, in a globalized economy, domestic legislations likely affect actors in third-party states via international trade.

This makes it particularly difficult for companies that have many points of contact with regulations, such as financial institutions and administrative units. They need to be aware of changes to their respective legal frame as soon as possible to make adequate adjustments, as non-compliance can be heavily sanctioned by official authorities.

Solution

AURELA is a joint research project based in Luxembourg, funded by the Ministry of the Economy and the National Research Fund. CURE Intelligence and the Luxembourg Institute of Science and Technology (LIST) have expanded their research partnership in the field of automated compliance and joined forces with LuxProvide and Governance Tailor to develop an AI system based on recent advances in Large Language Models (LLMs) and multidimensional graph theory.

It is designed to automate crucial tasks that are currently performed by lawyers and compliance officers. The system is trained to automatically structure, relate, and analyze legal documents that regulate common topics or objects. The target is to autonomously understand a legal frame, identify contextual legal requirements of involved actors, and suggest adjustments to ensure regulatory compliance.

As pilot domain of application, we consider anti-money laundering (AML) regulations. The legal frame of AML is frequently modified by authorities and affects a wide range of companies, such as banks, financial service providers, insurance companies, and art dealers. As a first service that can be performed by AURELA, we are developing a functionality for automated updates of existing AML policies. That is to say, AURELA takes an existing AML policy of, for instance, a bank, checks it against the current regulatory frame, and updates it such that it is compliant while providing a reasoning why particular changes were necessary.

Service Moduls

Ready-to-use
AI Tools

CURE AudienceLens:
Audience Intelligence with Digital Audience Twins

Branche

Diverse (e.g. consumer goods, healthcare, financial services & insurance, technology, telecommunications, public sector)

Aufgabe

Today’s organizations must make faster decisions than ever before. At the same time, audiences, markets, and customer expectations are constantly evolving. While traditional market research provides valuable insights, it is often expensive, time-consuming, and only available at specific points in time.

Marketing, communications, and product teams regularly face questions such as:

  • Which messages will resonate most with our target audience?
  • How will a campaign be perceived before launch?
  • Which product concept has the greatest potential?
  • What are the current needs, expectations, and concerns of our customers?
  • How can we make decisions based on evidence rather than assumptions?

 

Without reliable audience intelligence, organizations risk inefficient campaigns, misallocated budgets, and products that fail to meet market expectations.

 

Solution

CURE AudienceLens

With its fully automated Media Review, CURE Intelligence offers a scalable solution that combines advanced language processing technologies and data-driven models to deliver high-quality content – completely without editorial intervention.

How it works:

1. Audience Modeling

AudienceLens combines data from market research, social listening, customer insights, surveys, industry knowledge, and proprietary datasets to create AI-powered audience profiles.

2. Digital Twin Creation

The system generates realistic digital representations of customer segments, stakeholders, or buyer personas that reflect real-world audience characteristics.

3. Interactive Audience Testing

Users can ask questions, test campaign concepts, evaluate product ideas, validate messaging, and explore audience reactions through a conversational interface.

4. Insight Generation

AudienceLens delivers structured feedback, identifies opportunities and risks, highlights audience preferences, and provides actionable recommendations.

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