AI saves significant time on repetitive, text-heavy work: classifying incoming requests, summarising long documents, drafting product descriptions, giving the first reply to customer questions.
For the gain to be real, the task must be measurable. Projects that start with "let's add AI" usually end in a demo; those that start with "this task takes two hours a day" pay off.
What's included?
Needs analysis and suitability assessment
Model selection and cost estimate
Integration with existing systems
Question-answering infrastructure over your own data
Defining the steps that require human approval
Usage and cost monitoring
How we work
01
Task selection
How long each task takes is measured; the gain is calculated from that.
02
Small-scale trial
A limited pilot is run with real data.
03
Accuracy measurement
How much of the output needs correction is counted.
04
Integration
If it proves to work, it is placed into the existing flow.
05
Monitoring
Cost and accuracy are tracked continuously.
What determines the price?
Since every project is different, we don’t give a single list price. The items that determine the quote are:
Volume of data to process and model usage cost
Number of systems to integrate
Whether training/retrieval over your own data is needed
Complexity of the human-approval flow
Frequently Asked Questions
For business use we prefer configurations that prevent this. Which provider works under which terms is put in writing at the start of the project.
That's why we define the steps requiring human approval from the start. We don't recommend full automation for outputs that go directly to the customer.
Since pricing is per use, it depends on volume. The pilot lets us estimate the monthly cost with real data.