[ Tech stack ]
Vertex AI
Google Cloud's managed ML platform, from custom training to Gemini models.
Vertex AI brings together notebooks (Workbench, Colab Enterprise), custom or AutoML training, Vertex AI Pipelines (managed Kubeflow Pipelines), the Model Registry, the Feature Store and online and batch prediction endpoints with drift monitoring, all in one service. Model Garden gives access to Gemini, open models (Gemma, Llama) and their fine-tuning, and everything plugs natively into BigQuery and Cloud Storage. It's our choice when the data already lives in BigQuery, or when a project combines classic ML and generative AI on Google Cloud.
[ Why Vertex AI at Dexon ]
What this technology does well, and why we use it.
Typical usage: ML on BigQuery data, Gemini and RAG applications, forecasting, vision and recommendation.
- 01
Model Garden: Gemini, Gemma, Llama and partner models, fine-tuning included.
- 02
Pipelines: managed Kubeflow Pipelines, no cluster to run, artifact lineage.
- 03
Feature Store and BigQuery ML: features stay in the warehouse.
- 04
Online and batch endpoints with built-in drift monitoring and explainability.
[ Complementary technologies ]
The building blocks we often mobilise alongside.
A stack rarely exists alone. Here are the technologies Dexon most often pairs with this one, through pipeline habits, usage similarity or internal mastery. Click on a building block to see its scope.
[ Reassurance ]
- 0+
- custom projects delivered
- 30
- engineers, designers, project managers
- 80 %
- from top French schools
- 24 h
- average reply time
[ They trust us ]
More than 100 French and European companies trust us
[ Press ]
They talk about us.
Nationwide coverage by BFM Business, Le Figaro, Challenges, La Tribune and CNews. An outside reading of our work and our innovations.
