Services · Monte del Gallo
Data systems
Analytics, reporting layers and integrations that make decisions clearer.
Data-driven decisions
Every business generates data, and few know how to use it. We bridge that gap by building pipelines, dashboards and AI models that turn your data into a strategic advantage. The goal is to make decisions clearer, not to add another tool to look at.
What we deliver
- Business intelligence: custom dashboards and reports that give stakeholders real-time visibility into KPIs and trends.
- Data engineering: ETL pipelines, data warehouses and streaming architectures that keep your data clean and accessible.
- AI and machine learning: recommendation engines, NLP, computer vision and predictive models integrated into your products.
- Analytics platforms: end-to-end solutions, from data collection to interactive visualization and automated reporting.
Our own projects use the same building blocks. Gestione Immobili shows occupancy, income against expenses and return per property on a financial dashboard with an interactive map, and Soshiki brings revenue, collections, margins and expenses together for the businesses that use it.
How we work
- Audit. We assess your current data landscape, with its sources, quality and gaps, and define the opportunity.
- Strategy. We design the data architecture, choose the models and set success metrics aligned with business goals.
- Implementation. Pipelines, models and dashboards are built iteratively, with validation at every stage.
- Insights. Ongoing monitoring, model retraining and optimization keep your data delivering value.
Tools of the trade
- AI and ML: TensorFlow, PyTorch, scikit-learn, Hugging Face, the OpenAI API and LangChain.
- Data pipelines: Apache Airflow, Kafka, Spark, dbt and Celery.
- Visualization: D3.js, Plotly, Metabase, Power BI and Grafana.
- Storage: PostgreSQL, BigQuery, Snowflake, ClickHouse and S3.
Frequently asked questions
What can you build with our data?
A recommendation engine, a predictive model or a real-time analytics platform: we combine engineering rigor with machine learning expertise to deliver results you can measure.
Where do you start?
With an audit of your current data landscape: sources, quality and gaps. That defines the opportunity before we design the architecture and choose the models.