AI-Driven Customer Engagement

Crédit Mutuel Factoring selected dakAI, a specialist in bespoke AI solutions, to develop and implement a next-generation customer service solution powered by advanced conversational AI.  The project focused on deploying intelligent virtual assistants, capable of understanding natural language and engaging in contextual conversations with clients.  This collaborative effort leveraged dakAI's expertise to create a tailored solution aligned with Crédit Mutuel Factoring's specific needs, and those of VSEs and SMEs :

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Phase 1 - Understanding the customer journey and defining use cases

dakAI's team worked closely with Crédit Mutuel Factoring to map the customer journey, identify key pain points, and define the most impactful use cases for the virtual assistants.  This included analyzing call center data, reviewing customer feedback, and conducting workshops with customer service representatives.

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Phase 2 - Developing custom AI-powered virtual assistants

dakAI developed bespoke conversational AI models, leveraging advanced natural language processing and generative AI techniques.  These models were trained on a vast corpus of data, including past customer interactions, FAQs, product documentation, and specific factoring processes, enabling them to understand a wide range of inquiries and respond accurately and appropriately.  The virtual assistants were designed to handle common requests, such as balance inquiries, invoice status updates, payment information, and to guide clients through various factoring services. These agents have been specifically trained to accompany and support VSEs and SMEs. They guide them and provide advices on the best solutions.

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Phase 3 - Omnichannel integration and continuous improvement:

The virtual assistants were seamlessly integrated into Crédit Mutuel Factoring's website, mobile application, and other digital channels, providing 24/7 availability and a consistent user experience.  A robust feedback mechanism was implemented to continuously monitor the performance of the virtual assistants, identify areas for improvement, and retrain the AI models with new data, ensuring ongoing optimization and adaptation to evolving customer needs. The platform is designed to scale and to handle the specific, and sometimes complex, needs of VSEs and SMEs.

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