Artificial intelligence enriches Trendeo data

The databases 📊of my company, Trendeo, collect quantified information, mainly in terms of jobs created or eliminated, fundraising and amounts invested (CAPEX), in France and worldwide🌍. 👇🏻

The online application 💻 already provides data by region and sector, in various forms of maps, graphs, lists. The quality of our data enables us to create specific indicators. Several of our customers and prospects are already working on identifying 🔍 dynamic regional clusters, forecasting plant creations, spotting prospects or anticipating difficulties.

📈 We ourselves are working on creating complementary indicators (forecasting job creations or deletions 👨🏼‍⚕️).

🤖 This creation of indicators comes under a branch of AI with random forest type algorithms. Another possible use of AI, with a more familiar LLM-based approach, allows us to envisage a conversation 🗣️avec the data.

🎥 Below, a presentation video in which an agent, created with Dust, is asked to comment on the data in our France database for 2009.

🧠 He easily enough (although you have to grope a bit to get the right answer) gave answers that were both numerically correct, with contextual elements and often relevant comments.
The exercise of projecting employment forecasts for the automotive sector 🚗 in 2010 from 2009 data (2010 data was not provided to him) is impressive.

⚠️ Even without trusting it 100% (definitely not!), it can bring out both basic answers but also accompany them with relevant contextual comments, suggesting further investigation.

🎮 Enough to make you want to play with Trendeo data and AI! Check out the video below if I've managed to pique your interest, and let me know what you think!

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