01 / Process
From vague problem to workable task
A strong first use case has a recurring trigger, a clear output and someone who can judge exceptions. That prevents building a polished but detached AI layer.
AI implementation cost
What does AI implementation cost? The workflow defines the answer.
AI implementation is not an off-the-shelf product with one fixed price. The cost follows from the process you want to improve, the systems around it and the level of control required. That is why we make the first scope small, concrete and testable.
Scope
Where the budget actually goes.
02 / Systems
Context from the right sources
CRM, ERP, ticketing, documents, inboxes and databases determine how much context an agent needs and how reliably that context is available.
03 / Control
Autonomy is a design choice
Reading and proposing is smaller than executing actions or writing data back. Rights, logging, approval and escalation belong in the scope.
Decision
A useful price starts with boundaries.
A sound estimate is not a number from a brochure. It is a decision about what the first version does and does not need to do, and how to build safely from there.
Small first build
A clear process, limited number of sources and an agent that reads, structures or prepares proposals for a team.
Broader implementation
Multiple systems, complex exceptions, write actions, roles and a wider operational workflow.
Ongoing cost
Monitoring, evaluation, system changes, user feedback and managing exceptions after launch.
01-04
How we make cost concrete before building.
01
Choose a process
Not AI in general, but a recurring workflow where waiting, searching, checking or retyping is visible.
02
Set the first boundary
We define what the AI reads, what output needs to be useful and which actions remain with a person.
03
Check systems and data
We assess reachable sources, required rights and where data is incomplete or conflicting.
04
Make a build decision
You get a reasoned first scope: what to build, what belongs later and which conditions need work first.
FAQ
Frequently asked questions about AI implementation cost.
Why is there no fixed price on the site?
Because an AI agent or custom AI software is built around a specific process, existing systems and responsibilities. A fixed amount without that context would create false certainty.
What makes an AI implementation more expensive?
Mostly additional integrations, messy or inaccessible data, complex exceptions, actions with customer or financial impact and higher requirements for logging, rights and operation.
Can you start small?
Yes. The sensible first version touches real work but is deliberately bounded: one process, one owner, clear input and human review where needed.
What comes out of a Quickscan?
A concrete view of process, systems, risk, first scope and whether building makes sense now. Sometimes the answer is that the process needs to become sharper first.
Next
Do not separate scope from the process.
Contact
Process, data, build
Start with the Quickscan.
In a short analysis we look at your processes, systems and data. Afterwards you know where AI can add value and which solution is logical to build first.
Coverage
Working across Europe
Hours
Mon-Fri · 09-18 CET
E-mail
hallo@silvant.ai
First step
Quickscan