Data, models and intelligence.From architecture to deployment.

We build ML models that work with real data in production environments. We cover the full chain: from data exploration and algorithm selection to API deployment, drift monitoring and automatic retraining when the model starts to degrade.

We work across the full spectrum of modern ML: deep neural networks, Random Forest and Gradient Boosting (XGBoost, LightGBM) for tabular problems, LSTM and Transformers for time series with long dependencies, and ensembles when a single model is not enough.

When the problem requires it, we add quantitative risk analysis with Monte Carlo and VaR, or probabilistic scenario simulation for critical decisions.

We design and implement data architectures that work in production. From the ingestion of heterogeneous sources to the consumption layer for ML and analytics.

We handle structured, semi-structured and unstructured data — APIs, PDFs, relational databases, real-time streams, satellite imagery — all unified in a governed data lake with full lineage.

Every pipeline includes monitoring, automatic alerts and failure recovery. If something stops working, the system detects it and recovers without manual intervention.

We build AI agents that understand a complex task, plan the required steps, execute actions on real systems and deliver a verified result — without human intervention at every step.

These are not chatbots. They are autonomous systems that read documents, query data, make decisions with business logic, generate content and integrate with the systems you already use.

We choose the model and the deployment mode based on the case: European cloud when privacy allows it, on-premise or private cloud when data must stay inside your environment.

We build complete platforms where data, models and interfaces work in coordination: from IoT sensor ingestion to a navigable digital twin that supports real-time decisions.

A digital twin is not a pretty visualisation — it is a functional replica of your process, fed with real data, running predictive models and able to simulate future scenarios before applying them in the physical world.

Cloud-native architecture with high availability, deployed on your own infrastructure or on European cloud — without lock-in to a single provider.

We integrate ESA Copernicus data — including Sentinel-2 imagery — into analysis pipelines that produce actionable territorial intelligence.

From spectral indices that reveal vegetation health, water stress or land use change, to temporal analyses that surface trends invisible to the naked eye.

This data is combined with ML models to anticipate harvests, detect environmental anomalies, optimise the use of agricultural resources or monitor distributed assets from space.

We deliver blockchain solutions that turn traceability into a real competitive edge: from raw material origin to the end consumer, every step is recorded immutably, verifiable by any party and without dependence on a central intermediary.

It is not just technology — it is the ability to prove what you claim: that your product is what it says it is, that your processes meet the standards you certify, that your sustainability data is real and auditable.

We integrate blockchain with the data systems, IoT and digital platforms you already run, adding a trust layer without replacing your existing infrastructure.