Week 1
You choose the question
We start with a specific Finance question and define the target, baseline and decision criteria together.
- One clearly defined workflow
- A measurable starting point
- An economic target
Approach
You choose a specific Finance question. We build the proof on your data, measure it against the baseline and deploy the solution with the same team into live operations.
Week 1
We start with a specific Finance question and define the target, baseline and decision criteria together.
Weeks 1 to 3
We connect the relevant sources, map rules, exceptions and approvals, then build the proof on a defined data sample.
From week 3
After three weeks, you have the result against the baseline. If it fits, the same team deploys the solution and remains accountable for the production output.
The exact duration depends on the use case, integrations and operating scope.
ROI is defined in time, errors, cycle time, margin or cash impact before the build.
You see outputs, controls and exceptions on your data instead of in a presentation.
Impact, integrations and operating effort are clear before rollout.
Data quality
We first create a shared data foundation for the selected workflow. Sources, definitions and responsibilities become visible before AI assesses patterns or prioritises exceptions.
This avoids another parallel solution. The logic is embedded in the live Finance process and every output remains traceable to its source.
3 weeks
from use case to measured proof
10 weeks
until the first AI solution runs in production
Under 20 hours
of your team’s time per workflow
Fixed price
agreed before we start, one entity, one process