[ Tech stack ]
Python
The universal language for data, business scripts and AI.
Python combines a clean syntax, an unrivalled scientific ecosystem (NumPy, Pandas, PyTorch, scikit-learn) and native integration with the main data orchestrators. We use it for pipelines, AI experimentation, automation and backend services where productivity matters most.
[ Why Python at Dexon ]
What this technology does well, and why we use it.
Typical usage: Data pipelines, custom AI models, business APIs, automations.
- 01
The most mature data / AI ecosystem: PyTorch, TensorFlow, scikit-learn.
- 02
Fast iteration: from Jupyter notebook to a FastAPI service in production.
- 03
Exemplary readability, maintenance by mixed teams.
- 04
FastAPI, Pydantic, Polars: modern tooling, solid performance.
[ 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 brick to see its scope.
[ Reassurance ]
- 0+
- custom projects delivered
- 30
- engineers, designers, project managers
- 80 %
- from top French schools
- 24 h
- average reply time
[ Our AI stance ]
AI-augmented approach, supervised by experts.
We use artificial intelligence as a lever for acceleration and optimisation within our technical processes, while keeping strong human oversight on every strategic phase of the project.
AI improves productivity. It does not replace:
- field experience
- architectural expertise
- understanding business stakes
- technical governance
- complex trade-offs
- cybersecurity
- operational accountability
Our teams act as a layer of validation, quality control, security hardening and steering, to ensure reliable, scalable deliverables that can operate in real-world environments.