Business cases
Customer case & references
For 3 years, we have been building solutions with our customers that change and facilitate their daily lives.
Your questions, our answers
All the answers to understand our approach, how we work and what you can expect from our collaboration.
In which sectors has Diametral already supported its customers on AI and data projects?
Diametral operates in a wide variety of sectors where AI and data provide real business value. Among our customer references, we find in particular:
- The pharmaceutical industry (assistance in the discovery of new drugs)
- Pharmaceutical distribution (supply chain optimization)
- Insurance (prediction of agricultural yields for drought insurance)
- Luxury cosmetics (scoring and skin analysis with explanation of predictions)
- Major consumer groups (in-depth analysis of customer needs)
And projects related to the detection of trends on social networks.
Each project is tailor-made to meet a concrete business challenge.
Can you give us an example of a business case where AI has made it possible to go beyond traditional methods?
Yes, for example in the case of a pharmaceutical laboratory: the manual search for new molecular combinations in millions of medical publications had reached its limits. Diametral has built a dedicated AI system that makes it possible to quickly identify potential patentable combinations, thus greatly accelerating the drug discovery process.
How does Diametral transform social media data into a competitive advantage for its customers?
In a market where consumer behavior is changing very quickly, one of our customers needed to anticipate trends rather than suffer from them. We have developed a platform that transforms the “noise” of social networks into clear and usable actionable signals, allowing the client to make faster and better informed strategic decisions.
What concrete results can we expect from an AI/Data project with Diametral?
The results vary depending on the challenge, but our customers generally get:
Solutions that move from a Proof of Concept to successful industrialization (e.g.: customer needs analysis platform deployed on all French entities of a large group)
Operational transformation (complete optimization of the supply chain, prediction of agricultural yields making a new product insurable)
Better transparency and explainability of AI models (as for skin scoring in cosmetics, usable in stores and on mobile)
The objective is always the same: to build tools that really change the daily life of teams and create sustainable business value.
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