General AI failed to parse 6,000 complex budget codes. A custom model now maps every line to green goals, cutting manual work by 30%.
A French municipality with a population that triples to 250,000 in summer manages 6,000 annual budgetary operations across diverse public services.
A new law mandated the classification of every budget line against environmental goals, but manual Excel processes were error-prone and unscalable....
“The ‘green’ budget is a perfect use case because it’s mandatory, time-consuming, and requires an understanding of French and the business context. General-purpose AI would produce poor results, as it doesn’t recognize budgetary codes or the acronyms we use. So, we had to train a specialized model—tiny LLMs—which works perfectly.”
Municipal government and public administration for the city of Antibes.
Data policies blocked collaboration. Federated AI detects signals 10x faster, syncing global observatories without exposing raw data.
Drowning in 80,000 monthly alerts, analysts struggled to secure data. AI now prioritizes threats, cutting response time by 99%.
Manual pivot tables missed complex fraud rings. A graph database now links scattered evidence, cutting investigations from weeks to minutes.
100 manual touchpoints caused 12-day backlogs. AI now validates IDs and disburses funds autonomously, cutting processing to 30 minutes.