01
Documents ready for review
Read requests, attachments or forms; extract what matters; prepare a draft; ask for confirmation when a fact is missing.
Quote requests, initial data collection, applications, reports and contracts under review.
AI automation in Italy
AI automation built around the work people actually do.
I look at the work piling up, what slows it down and who handles it. We then choose which steps to automate, with clear checks for errors and cases that need a person’s decision.
For founders, operations leaders and teams in Italy who want to improve an existing process.
Where AI can reduce the team’s workload.
Automation is useful when it performs a specific task, uses reliable data and knows when to ask a person for help.
02
Requests to read and route
Classify requests, add the information needed and send them to the right person. Flag uncertain cases for review.
Shared inboxes, support tickets, potential customers, supplier requests and urgent cases.
03
Systems that do not talk
Connect the tools already in use, avoid copying information by hand and keep track of where the data comes from.
CRM, ERP, email, spreadsheets, databases and internal portals.
Five questions before you spend a euro.
Before investing, we need to understand whether the process is suitable for automation. These are the questions I start with.
Does the work repeat often enough to observe?
Good signal: Real cases, examples and a recognisable frequency exist.
Caution: The process changes every time and nobody describes it the same way.
Is the required data accessible and trustworthy?
Good signal: We know where the data is, who can use it and who corrects errors.
Caution: The data lives only in people's memory or files with no history.
Can you recognise cases that need a person?
Good signal: We know when the system must stop and who needs to decide.
Caution: The implicit goal is to automate everything, including ambiguous cases.
Can we measure the current work to compare it with the automation?
Good signal: We have starting figures for time, errors, waiting or workload.
Caution: Success is described only as innovation or using AI.
Will someone look after the process after launch?
Good signal: A person owns the rules, exceptions and improvements.
Caution: The system is expected to run alone without maintenance or decisions.
If three or more caution signals appear, first clarify how the process works and gather the missing examples and data.
Fifteen years building software people rely on.
I have spent fifteen years building software with real users, incidents, deadlines and consequences: from London startups and Amsterdam fintech to AI systems and applied-AI teaching at SDA Bocconi. I bring the same discipline to business automation.
- 15+: years in software engineering
- Seed → IPO: product leadership through a public listing
- 3.2★ → 4.7★: App Store rating during the team's work at bunq
- SDA Bocconi: two sessions on applied and agentic AI
These results describe my experience. For your project, we define goals and measures around your company’s process.
Understand the process, build the system, check the result.
Each stage has a clear result we check before moving on.
01
Observe
We reconstruct the work as it happens: inputs, decisions, waiting, manual steps, exceptions and current cost.
You receive: a process map and starting measurements.
02
Define the work
We choose what to automate, what remains human, which data is allowed and where the system must stop.
You receive: agreed activities, responsibilities and verification criteria.
03
Build
We connect systems and record their actions. We also test failures and how to return to the previous state.
You receive: automation to test in a controlled environment.
04
Check the result
We compare the new process with the starting measurements. Reductions in work, waiting and risk guide the decision on whether to expand it.
You receive: a comparison of results and a recommendation on what to do next.
When it is worth getting started.
It is worth a conversation when
- a process consumes hours every week or slows revenue and service;
- the team already uses digital tools but spends its time copying and checking;
- errors or waiting have a recognisable cost;
- you are willing to start with a small scope and test it properly.
It is probably too early when
- you want an AI feature without a precise operating problem;
- nobody can show real examples of the work;
- the process has no accountable owner;
- the project requires removing every human check on day one.
Understand what AI should do, and where it should stop.
The guide starts with a quote request and follows every step: what AI interprets, which facts come from company systems, when an exception returns to a person, and how to test the idea on ten real cases.
What is worth clarifying early.
What does an AI automation company actually do?
It studies a process and chooses which tasks to automate. It connects data and tools, handles errors and cases that need a person, then compares the result with the previous process. Testing and post-launch management are included as agreed for the project.
How much does an AI automation project cost?
It depends on data access, the number of systems involved and the risk of the actions. When the use case is not yet defined, the AI and automation diagnosis costs €10,000 excluding VAT. When the use case is already chosen, an AI pilot project starts at €18,000 excluding VAT. The written proposal defines the work included.
How long does it take?
The AI and automation diagnosis takes two weeks. A bounded AI pilot project usually takes four to six weeks. A broader rollout is estimated only after the process, integrations, exceptions and pilot result have been verified.
Do you work with Italian companies from Amsterdam?
Yes. I am Italian, work in Italian and keep Italian working hours; Italy is the primary market. The Dutch base is the legal and operating home of DL Solutions, not a barrier to working with teams in Italy.
Do we need to replace the software we already use?
Usually not. The first goal is to use what exists more effectively by connecting systems and data with clear ownership. A tool is replaced only when the constraint is demonstrated, not to make the project look more impressive.
Which part of the work would you like to improve?
Tell me what is piling up, who handles it and where you get stuck. I read every request and reply within 2 business days.