Our projects

Optimized planning in production #manufacturing
To make manufacturing processes more efficient, we have developed an AI solution that calculates the most effective and efficient planning and scheduling for each production line.
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Often the production planning process is done manually, with multiple associated risks. Our Anagram AI solution can optimize the planner’s work, providing the best schedule for each machine, within existing constraints and rules.

Planning time is drastically reduced, with better machine saturation and more efficient management of production resources.

Results

– 30% FTE* on the planning process (*full time equivalent)
+ 9% Saturation level of production machines 

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Extracting information automatically #banking
A Natural Language Processing solution enables extracting and connecting key information from documents, saving time.
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The process of analyzing court reports involves manual activities of visual inspection and information extraction, often with scarce resources available. Being able to automate this activity saves time and improves the final service.

Our Adoc solution, born from the combination of NLP and Information Extraction, automates the end-to-end process, from receiving the text to compiling the final file with the crucial information.

Results

– 90% Document processing time compared to the past
500+ Documents processed weekly
2 million Documents digitized, usable by the business, compared to the past

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Improving the online user’s experience #editorial
How to reduce the user's abandonment rate from an App? Using an AI engine, it is possible to generate "user-based" content that improves the customer's journey of the customers' base.
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Creating effective content for users means meeting their interests over time. To do so, a customer’s journey must be developed that is close to his or her current and future needs.

Using a mix of AI algorithms, it is possible to predict users’ interests and behaviors, identify the optimal actions and content to propose, and maximize the effectiveness of marketing campaigns, progressively reducing the abandonment rate.

Results

+ 80% correctly profiled interests
70% accuracy of churn risk prediction

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Optimizing store assortment #retail
In order to no longer have under/over stock problems, we have implemented an AI project to plan merchandise in stores based on sales trends.
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In the multi-store environment, stock planning is crucial to be able to cover the demand for products in a timely manner and to improve sales.

AI algorithms can determine the right strategy of action: on the one hand, the amount of merchandise needed from week to week is suggested; on the other hand, sales and promotional campaigns are monitored.

Results

– 30% decrease in remaining stock on a weekly basis, for specific merchandise functions

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