Operational Intelligence Dashboard
Fragmented sources. One executive view.
ERP, quality, suppliers, customers and sustainability — converging into a single, always-current operational picture.
Read the case studyAlessandro Fabiano
Digital products, enterprise systems, artificial intelligence and technology strategy designed around real operational needs.
Technology Leader · Digital Product Builder · AI & Systems Architect
I work where technology, operations and business strategy meet.
Enterprise infrastructure, intelligent software, data platforms, automation and AI-enabled products — the common thread is turning fragmented processes into coherent systems.
Platforms people actually work in.
Applied AI that supports real decisions.
The backbone that keeps an organization coherent.
Scattered data turned into actionable indicators.
Security as an architectural property.
Roadmaps aligned with where the business is going.
Three systems designed, built and operated in real enterprise contexts. Projects are presented by function, with anonymized interfaces and abstracted data.
Fragmented sources. One executive view.
ERP, quality, suppliers, customers and sustainability — converging into a single, always-current operational picture.
Read the case studyFrom a message to a governed, auditable record.
An incoming request becomes a structured ticket: classified, prioritized, summarized and drafted — by an isolated AI layer that assists people.
Read the case studyRules in. Validated output out.
Technical inputs pass through explicit rules and compatibility validation, and come out as a structured commercial document.
Read the case studyEvery engagement follows the same arc: a business need becomes a process, a process becomes an architecture, an architecture becomes a product people adopt — and the loop starts again.
People, processes, constraints and objectives — before any technology choice.
The system: data, integrations, security and its evolutionary path.
Strategy turned into products, automations and operational platforms.
Measure impact, improve the system, integrate it into how the company works.
Alessandro Fabiano works across technology leadership, digital product development and enterprise transformation. His experience combines hands-on implementation with strategic responsibility, bridging infrastructure, software, data, artificial intelligence and operational processes.
The through-line is ownership of the full arc: from the first conversation about a business problem to the running system — and its governance afterwards.
A publication series in preparation for Zenodo and LinkedIn: large language models, retrieval-augmented generation, the Model Context Protocol and AI companions.
The series continues — new links and DOIs appear here with each release.
A ~24-month design-science case study in regulated manufacturing: formalising rules, data, documents and accountability into interoperable platforms before applying RAG, agentic AI and private LLMs to QA/QC, supply chain and vendor documentation.
DOI: 10.5281/zenodo.21314763PublishedEmbedding LLMs into real operational workflows — classification, summarization, drafting — with governance, isolation and auditability as first-class requirements.
In draftingGrounding language models in company knowledge: retrieval design, data quality, evaluation and the failure modes that matter in production.
In draftingHow MCP standardizes the connection between AI agents and enterprise tools — and what that means for agent systems that are useful, secure and maintainable.
In draftingMemory, personality, boundaries and trust. This research underpins an application that will be presented in a dedicated publication.
UpcomingI publish my research openly and collaborate on selected projects: joint R&D, applied AI, operational intelligence and ambitious digital systems. If you are working on something serious, let’s talk.