Services

SubAlpine.IT supports companies, laboratories and public institutions in the design and implementation of data-driven solutions. Each mission starts from your actual need — not from a technology looking for a problem.

Machine Learning & AI solutions

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Design, development and deployment of machine learning models adapted to your use case:

• Supervised and unsupervised learning (classification, regression, clustering)
• Deep learning architectures for image, signal and structured data
• Reinforcement learning for sequential decision-making problems
• Model auditing, robustness evaluation and noise characterisation

Data Science & statistical analysis

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Turn your raw data into reliable, actionable knowledge:

• Data exploration, cleaning and feature engineering
• Statistical modelling and hypothesis testing
• Dashboards and visualisations to support decision-making
• Reproducible analysis pipelines

Optimisation

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Reduce time, cost and resource consumption of your processes:

• Metaheuristics and local search methods for complex combinatorial problems
• Trade-off analysis between solution quality and computation budget
• Integration of optimisation loops into existing workflows

Software development

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Beyond data-centric work, SubAlpine.IT designs and builds complete software products:

• Backend development in Python (FastAPI), REST APIs and third-party integrations
• Relational and geospatial databases (PostgreSQL, PostGIS)
• Cross-platform mobile and web applications (Flutter)
• Packaging, deployment and operations (Docker, CI/CD, Nginx)

Scientific consulting & R&D

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Benefit from an academic research background applied to industrial problems:

• State-of-the-art reviews and feasibility studies
• Prototyping of novel methods and proof-of-concept development
• Scientific writing, publications and grant proposal support

How a mission unfolds

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1. Understand — a first exchange to frame the need, the data and the constraints.
2. Assess — a short study to validate feasibility and select the right method, at the right scale.
3. Build — iterative development with regular checkpoints and measurable objectives.
4. Transfer — documentation, training and handover so the solution lives on without dependency.