The market rewards whoever is best in a specific context, not whoever covers many sectors equally. Here is who we serve and, at the bottom of the page, who we do not serve yet.
The parameter is not how many people you are, but where knowledge stops today. A structured IT department is not a requirement.
Few mapped processes, tools that do not talk to each other, the feeling that every project starts over.
The first Brain and the first measured process: a verifiable result, not an announced transformation.
A high-volume manual process.
An IT contact in place, systems already running, several departments producing data nobody has time to cross.
Orchestration across several Brains, with cross-department conclusions reaching whoever has the overall view.
A case across two departments that barely talk.
Explicit confidentiality requirements, a DPO involved from the first conversation, and a no that stops everything.
A dedicated model or one on your own infrastructure, isolation per organisation, an audit trail on every operation.
A sensitive document process, with separate per-Brain permissions.
These priorities say where it makes sense to begin, not which sectors to cover all at once. The percentages are Eurostat AI adoption data by sector, 2025.
A wide base of European SMEs, with repetitive and measurable processes: quality control, order handling, maintenance, quote preparation.
PriorityThe most natural ground for the first vertical case, and the sector of the case we publish.
Work where the value is the knowledge itself, and where know-how has to be preserved when people change role or company.
CautionA market more exposed to general-purpose tools: it needs a concrete use case, not a category promise.
A lot of unexplored ground, with highly repetitive processes: order handling, tracking, transport documentation.
CautionDigital maturity is often lower: it has to be checked case by case whether the minimum tools to connect to exist.
The conclusions that come from crossing several Brains serve whoever has the cross-department view. In smaller companies that is often the same person who signs.
A number and a time to break even, not a vision.
“What does it cost, and when do I see it.”
The Proof of Value produces the number before the investment. In the Smart Quoting case: payback in about five months, a working system in six weeks.
That it starts from a real process, without overhauling the existing stack.
“How does it fit with what I already have.”
Connectors attach to the tools in use through MCP, REST APIs or webhooks. No migration: where there is nothing to attach to, an app is activated on that single process.
That daily work gets simpler, with answers from the right context.
“I have to change how I work.”
For almost everyone the change is that the tools they always used start answering better. A new environment opens only where a process earns it.
Hours saved and aggregate return, with a method that holds up over time.
“Whether the claimed savings are real.”
The calculation models are versioned: inputs, sources and formula are stated. The return shown in a meeting is still verifiable months later.
Where the data sits, who accesses what, how every operation is logged.
“Where does our data end up.”
European infrastructure, isolation per organisation, per-Brain permissions and an operations log. No third-party model training on your content.
A path that does not pay for itself suits neither of us. These are the cases where we say so upfront, rather than discovering it in month three.
DBRAINS starts from a mapping. For an immediate answer on a single document a general-purpose tool is faster, and there is no reason to pay for a path.
On reading and summarising, the gap with general-purpose tools has closed. What we add is per-domain permissions and cross-department conclusions: if you do not need those, you do not need us.
The first number comes from there: without volume the return is too small to justify starting, and it shows in the Proof of Value already. Stopping there is a legitimate answer.
They have the lowest AI adoption, so in theory the widest margin. In practice that reflects a digital maturity that slows any platform down: for now they are not among our priorities.
Tell us about your context and a process to start from. We show you what would change, with numbers on your own case.