The research behind the decision layer.
Four white papers, written in a scientific register, on the problems Dimbo was built to solve. Each costs the problem with cited, published macro evidence, then models the firm-level consequence transparently — every number is either attributed to a named source or flagged as Dimbo analysis. No invented statistics. No unheld certifications. Representative firms only.
Europe's best mid-market firms under-adopt the technology that would make them productive (WP1) while their irreplaceable operational know-how quietly retires (WP2), and the AI that could save them is already leaking their data out of the perimeter (WP3) — because nobody built a system to collect and govern that data well (WP4). Dimbo is that system.
One argument, four papers.
Read them in order for the full thesis, or jump to the one that matches your role. Each links to its platform pillar and to the free Deadline Audit.
The Diffusion Gap
Europe's productivity problem is an adoption problem, not an invention problem. The frontier tools exist; the mid-market backbone — 99.8% of EU enterprises — can't reach them because the market for deployment is broken. Dimbo is a working deployment path.
Read paper → White Paper 02 · Read nowThe Silent Retirement
Italy has the oldest workforce in the EU and the most family-owned SMEs. The passaggio generazionale is the channel through which undocumented tacit know-how is lost forever. The answer isn't to hire faster — it's to capture faster.
Read paper → White Paper 03 · Read nowShadow AI
Your data has already left the building. Employees paste contracts, pricing and source code into public models with no governance — a daily exfiltration event colliding with GDPR, the EU AI Act, NIS2 and Schrems II. The remedy isn't prohibition; it's a sovereign, governed substitute.
Read paper → White Paper 04 · Read nowThe Value of Data
The data is the product; the interface is just an instrument. Dark data and poor quality carry a large unbudgeted cost — and foreclose the cross-silo joins where the non-obvious value hides. Collection quality, entity resolution and provenance are the moat.
Read paper →How we handle a number.
Real, published figures — Draghi, OECD, Eurostat, ISTAT, IBM, Gartner — attributed inline and in each paper's reference list. Used to anchor plausibility, never to assert a firm-level result.
Transparent firm-level arithmetic built on stated, changeable inputs. A CFO can dispute any assumption and re-run it — the logic is fully exposed, never hidden behind a headline.
We cost the problem with evidence, then apply a deliberately low capture rate for the value. The honest claim is "Dimbo removes avoidable losses," not "Dimbo eliminates all loss."
Stop reading about the problem. Measure yours.
The 48-hour Deadline Audit runs on a slice of your own data — open commitments, overdue invoices, expiring contracts, bucketed 30/60/90 days out with hard cash figures. No installs, no rip-and-replace, a human reply within one day.