Apps & AI
Assistants that carry a process end to end — draft quotes, extract data from documents, handle repetitive requests. Nothing leaves without a person approving it, and your data stays inside the European Union: the model runs on our own servers in Romania, not at an external provider.
Who this is for
An agent makes sense where the process is clear, repeats, and the final step needs a signature anyway.
Discovery notes are turned into a quote by hand, on every request. The structure is always the same; only the content changes.
Somebody opens the documents and emails one by one and copies the fields into a table. The work is identical every time.
Repetitive requests that need a correct answer, not a creative one. The answer already exists somewhere; the time goes into finding it.
What leaves the company has consequences: a price, a commitment, a piece of information about a client. You need automation that stops before sending.
What you’re losing now
Not the mistakes. The hours spent on something that does not require thinking.
The request arrives, but whoever can turn it into a quote is busy. The delay costs more than the hour of work itself.
Hundreds of fields copied by hand produce, statistically, a few wrong ones. Nobody knows which, so nothing in particular can be corrected.
A process that sends on its own can also send what it should not. That is why many companies stay manual — not out of preference, out of caution.
What you get
Six deliverables. The third is the one that makes the difference: approval stays with a person.
The agent reads the discovery notes and produces the quote in your format, with prices from your own catalogue. You check it and send it.
The fields you need come out of the documents and land structured where they are used, without anybody retyping them.
The agent proposes, it does not execute. Nothing leaves the company without somebody pressing approve, and what was approved stays in the record.
Questions that already have a correct answer get one, with the source cited. Anything outside the pattern goes to a person rather than to a guess.
The agent runs on a dedicated server inside the European Union, and the model on our infrastructure in Romania. No external AI provider.
What the agent proposed, what was approved, what was rejected and by whom. Without it, nobody could answer for what left the company.
How we work
We start with a single flow, the most repetitive one. The rest follow once that one works.
Duration:
You tell us which process repeats most and who does it today. We pick one — the one with the most volume and the least judgement.
The agent is built for the chosen process and you use it on real cases, with approval at every step. What does not work shows up in the first week.
The validated flow goes into use, with the record and the approval step. The next process is added on the same infrastructure.
Timing depends on how well the process is defined and how many systems have to be touched — we agree these after the proof-of-concept.
Evidence
The quote is written from scratch on every request, and full automation is too risky to be considered at all.
The agent drafts the proposal from the notes that already exist, in minutes. A person checks it and approves it — and what was approved stays in the record.
The comparison describes what changes in how you work, not the measured outcome of any particular project.
What stops you
From the same stage
Applications give the work structure, models anticipate it, agents carry it end to end.
We turn spreadsheets that outgrew themselves into web apps with a real database, multi-user access and no expensive licenses.
The way into AI: we assess what is worth automating at your company, build the smallest version on your real data and integrate it into what you already use.
Next step
Tell us which decision you want to make better. We’ll tell you whether we can help, and how, concretely.