AI & Machine Learning
From proof-of-concept to production, we build bespoke machine learning systems with robust MLOps pipelines, model validation and monitoring, ensuring reproducibility and operational quality.
FSB Solutions partners with established organisations to modernize operations, unlock data value, and deploy reliable AI at scale. We combine pragmatic strategy, engineering discipline and responsible AI practices to deliver measurable business outcomes.
From proof-of-concept to production, we build bespoke machine learning systems with robust MLOps pipelines, model validation and monitoring, ensuring reproducibility and operational quality.
Architectures designed for scalability and resilience: cloud migrations, containerisation, IaC and cost governance so your AI services run reliably in production.
End-to-end data platforms including ingestion, transformation, cataloguing and analytics — designed for performance, observability and compliance with EU regulations.
Implemented probabilistic forecasting to reduce overstock and stockouts, optimising working capital while improving on-shelf availability.
Built sensor analytics and event-driven pipelines that detect early failure signatures, schedule maintenance proactively and increase equipment uptime.
Automated document processing and extraction workflows that reduce manual review time and improve data quality for downstream analytics.
A cross-functional team of software engineers, data scientists and domain consultants. Our blended teams pair technical excellence with industry knowledge to deliver dependable systems.
Founder & CEO — strategy, partnerships and client outcomes
Head of Engineering — platform architecture and delivery
Lead Data Scientist — modelling, validation and governance
Lead Consultant - Digital Transformation & AI
We hire engineers and data practitioners for hybrid roles in Milan and remote positions across the EU.
Have a project or partnership in mind? Reach out and we'll schedule an introductory call.
Guides and frameworks for scoping pilots, selecting measurable KPIs and running experiments that de-risk broader rollouts.
Architecture patterns and operational practices for continuous delivery, monitoring and governance of machine learning systems.
Approaches to keep data initiatives compliant with GDPR while enabling analytics—data minimisation, pseudonymisation and robust access controls.