Process
Five steps. Your sign-off at each one.
We only move on once you have signed off the result of the previous step.
Diagnostic
We watch how the work is done today and measure the time spent on repetitive tasks.
Design
We design the agent or workflow, and set the metric that will tell whether the project worked.
Prototype
A first version tested on your real cases, within one to two weeks.
Deployment
Go-live, security testing and training for the team that will use it.
Improvement
Every month, we track the results and tune the agent to what it meets in the field.
We only move to the next step once you have signed off the result of the previous one.
What we measure
Results before technology.
Every project tracks one clear metric, chosen with you. These are the most common.
- Hours savedThe time your team no longer spends on the automated task, measured before and after.
- Messages handledThe requests the agent answered on its own, and those it handed to a person.
- Sales generatedOrders and appointments taken by the agent, tied back to the conversation they came from.
Our rules
What stays the same from one project to the next.
A metric before a line of code
The success metric is set at the design stage. Without it, nobody could say whether the agent pays off.
Your real cases, from the prototype on
The prototype is tested on your messages, your documents and your edge cases, not on a demo.
A human stays in charge
The agent knows when to hand the conversation to your team. It frees people up; it does not replace them.
Security before go-live
Prompt-injection tests, access control and logging are part of deployment.
Where should you start with AI?
The AI diagnostic finds the tasks that cost you the most time and tells you which ones are worth automating, before you invest anything.