An expense management chatbot that can identify elements of your answers, transcribe documents or voice messages and then interact with databases and create graphs for automated and efficient expense management. 

Goal: This integrated solution could help businesses and individuals manage their finances more effectively, by transforming raw data into actionable information and automating administrative tasks.

What's next: Make the bot capable of predictions, finding out abnormal expenses and building efficient planning expenses.

A chatbot for one of our partner's websites Q&As. This chatbot makes Q&As more accessible and interactive, enabling users to find answers to their questions in a fluid and natural way. 

Goal: Improve the user experience by reducing the time spent searching for information and offering personalised answers.

What's next: Connect your bot to you're own system and make it execute simple tasks.

A machine learning algorithm capable of predicting property prices in New Caledonia. This prototype, deployed on Microsoft Azure, is accessible via a graphical interface that allows users to interact with the model and obtain price estimates in real time. 

Goal: This application illustrates how ML technologies can be applied to provide concrete and useful solutions in the real estate sector.

An OCR engine based on google vision technology and LLM Gemini to analyze expense reports sent by users.

Goal: This engine aims to accelerate the process of sending expense reports and improve the user experience.

What's next: Analyse not only expense but other type of documents such as your own company forms.