Instead of choosing a tool and looking for a use case for it, we first check where time is actually disappearing in your company. You get a document with a recommendation and a pilot scope, not an offer for an implementation nobody has costed yet.
Who this is for
You know AI could help, but you don't know where. The topic is on the board's agenda, budget is provisionally set aside, but nobody can point to the process to start with.
You have several ideas and don't know which is best. The audit compares them against the same criteria: effort, risk, impact on day-to-day work.
A board rarely approves an investment based on the belief that "AI helps everyone now." The audit produces a document you can put on the table.
You've already received a quote and want to check it before deciding.
If you know exactly what you want, have the process documented and your knowledge organized, this stage can be skipped and you can go straight to the pilot. We'll say so directly if that's the case. The audit is not a mandatory gate before every conversation.
How we qualify a process for audit
What you receive
Written without technical jargon, so it can be read at a decision-making meeting.
Recommendation format
The recommendation isn’t a single sentence saying “we propose implementing X.” The decision stays with you, but it isn’t made blind. For each option we give effort, risk, and impact on the team’s daily work. An example recommendation scope:
We choose metrics to fit the process, not the other way around
At the audit stage we select two or three of them and set a baseline for each. Below are the ones that work most often.
From intake to closure.
How many still require rewriting data.
How long it takes to find the answer needed to do the work.
Mistakes arising from manual data entry.
Share of cases closed without involving another person.
Cost of handling one case, if it can be reasonably calculated.
What we don’t provide: results from other companies’ implementations presented as a promise for your process. A number pulled from a different context says nothing about your situation. We measure on your data, in your setting.
Two different services, worth knowing which one you need
If the problem is an existing application rather than a process, we start from the other path.
The starting point is the way work is done: a case, a document, a request, the flow between people and systems.
Answers the question: where is it worth improving the work.
Concerns a specific piece of software: its technical condition, security, architecture, and potential for further development.
Answers the question: is this application worth developing further, and what risks does it face.
Further implementation paths
This is settled in the recommendation, not after signing a contract. In every case there is one lead team and one point of contact. We don’t pass you between companies.
A short conversation after which you’ll know whether an AI implementation makes sense in your case.
