Custom AI and automation systems

First we understand the work. Then we build the AI that does it.

To be genuinely useful, artificial intelligence has to know your company: products, documents, rules, customers, tools and that one step that “only Marco knows how to do”. We design custom AI for B2B companies starting from a real process and building the right technology around it. Not the other way round.

The first conversation is free. No commitment and no 83-slide presentations.

Custom AI and automation
−68%
less time on repetitive tasks
11h
a week given back per person
4×
faster at preparing a quote
6 wks
from first call to system in use

Average values recorded across the projects we run, measured before and after automating the process.

The problem

AI can do a great many things. About your company, though, it still knows nothing.

A generic tool can write a nice email. It's harder for it to know which part number to use, where to find the latest datasheet, or why that customer always orders with a different tolerance.

It doesn't know your archives. It doesn't know the exceptions. It doesn't know which information it may use and which must be checked by a person. Our job is to give it the context, the tools and the rules it needs to become useful in your daily work.

We don't lay a layer of AI on top of problems that stayed the same. First we understand the mechanism. Then we make it smarter.

The first meeting

The first technology we use? A conversation.

You don't need to arrive with a solution already written. You don't even need to know whether you need an agent, an automation or something that doesn't yet have a particularly sellable name.

You tell us how you really work: where time is lost, where the same steps repeat, where errors pile up and where you constantly have to “ask the person who knows”.

The conversation is free. If there's a sensible project, we design it together. If it isn't worth it, we'll tell you: better a useful no than one more piece of software to maintain.

Let's have a chat
During the first conversation
we listen to your processes and your team's needs
we show you concrete examples and applications
we identify the tasks with the greatest potential
we suggest possible solutions, priorities and investment levels
we assess what is worth automating and what is better left alone
The solutions

What we build, in practice

It depends on the problem. And that's a far more serious answer than “let's build a chatbot”.

01

Custom artificial intelligence development

We build systems configured on your company's documentation, procedures and language. We connect them to controlled sources and define what they can do, what they must verify and when they must stop.

That doesn't necessarily mean training a model from scratch. It means building the right combination of models, data, instructions, software and controls.

02

Enterprise AI agents

Systems able to carry out multi-step tasks: read a request, look up information, prepare a document, update the CRM and ask for approval when needed.

The goal isn't to give suggestions faster. It's to move the work forward.

03

Business process automation with AI

We connect AI to the tools your team already uses: CRM, ERP, management systems, PLM, spreadsheets, mailboxes, databases and shared folders.

Yes, including that Excel file nobody dares open any more without making a backup first.

04

Proprietary B2B AI

When the project calls for it, we build software, knowledge bases, automations and interfaces dedicated to your company.

Data, proprietary components, third-party licences, documentation and transferability are clearly defined in the project and in the contract. No magic formulas and no creative asterisks.

05

Specific technical expertise

We configure the system with the terminology, materials, standards, certifications and procedures of your industry.

When an answer requires precise sources, the AI must be able to point to them. When it doesn't have enough information, it must say so. Inventing with great confidence is not technical expertise.

06

Environments built around people

We design simple interfaces and tools suited to the way the team actually works.

Because a system can be extremely clever, but if using it takes twelve clicks and a survival course, it will soon be replaced by the old spreadsheet.

Applications

Things AI can do while you do something else

These are examples, not a fixed menu. The solution always starts from the process.

Engineering department

Search historical archives, compare bills of materials, extract data from datasheets, prepare documentation and flag inconsistencies before they become problems.

Sales

Read a request, retrieve the necessary information, draft a quote, update the CRM and remind the salesperson what's missing to close the deal.

Customer service

First-level technical support using manuals, product sheets, request history and company procedures. Non-standard cases are passed to the right person, with the context already gathered.

Production and quality

Check documents, organise reports, verify that required information is present and improve traceability and access to batch data.

Marketing and communication

Turn technical information into product sheets, content, industry translations and sales material, keeping terminology and tone consistent.

Administration and back office

Classify documents, extract data, prepare summaries, route requests and reduce the copy-and-paste between tools that, for some reason, still don't talk to each other.

When it's worth it

We don't put AI everywhere. It isn't a garnish.

A process is a good candidate when

it happens often
it takes a lot of manual time
it follows recognisable rules
it uses information that is available
it generates errors, delays or bottlenecks
it can be measured before and after

It's worth pausing to think when

The task is extremely rare, completely unpredictable or too risky to be handled with adequate controls.

The question isn't: “Can we use AI?”. Almost always we can.

The useful question is: is it really worth it?

The method

From “we could” to “it actually works”

1 We listen and map

We talk to the people who do the work. We reconstruct steps, tools, exceptions, responsibilities and the points where the process tends to jam.

2 We choose where to start

We identify a process with concrete, measurable impact. First a useful result, then everything else.

3 We build a first version

We prepare a working prototype, connect it to the necessary sources and check answer quality, permissions and edge cases.

4 We integrate and put it to the test

We connect the system to your business tools and test it with the people who will have to use it. If it only works during our presentation, it doesn't work.

5 We train the team

We run hands-on training: how to use the system, how to check it, what to expect and when to involve a person.

6 We measure and scale

We compare times, errors, volumes and quality before and after. If the numbers add up, we extend the system or move on to the next process.

Data and security

Your data stays yours. That isn't the part written in small print.

Before choosing models and tools we define how data must be handled. We use services, configurations and contractual terms designed so that your company content is not used to train third-party general models. When requirements demand it, we can consider dedicated infrastructure or on-premise solutions.

Security isn't a badge you add at the end. It's part of the project from the start.

In the project we define
who can access which information
which data may be processed
where it is stored
retention periods and activity logs
steps that require human approval
ownership, licences and transferability of the solution
Results

If you don't measure it, it's just a demo that went well.

Before automating we define how to assess the result. We can measure:

Working hours saved
Error reduction
Time to complete a task
Response speed to customers and colleagues
Cases or requests handled
Backlog cleared
Actual usage by the team

AI is interesting. A process that takes half the time is far more interesting.

Let's talk

What's the thing your team still does with copy, paste and patience?

Tell us about it. We'll listen to how it works today, show you free of charge what we've already built and what AI can do in your case. Then we'll assess together whether there's a useful, sustainable and buildable solution.

If it can be automated, we'll find a way. If it isn't worth it, we'll tell you that too.

The first conversation is free and commits you to nothing.

Tell us where the work jams

Frequently asked questions

Do we already need to know what we want to automate?

No. It's enough to tell us where time is lost, where errors happen or which tasks the team would like to do faster. The solution comes later.

Do we need all our data organised already?

It helps, but it isn't essential. Part of the project can be putting order into documents, archives and knowledge spread across tools and people.

How long does it take to see a first result?

It depends on the process, the integrations and the quality of available data. For a well-scoped project, a first working version can be ready in a few weeks. After the initial analysis we define realistic phases and timings.

How much does a custom AI project cost?

It depends on complexity, integrations, security requirements and the level of autonomy required. After the first free conversation we prepare a phased proposal, with costs, objectives and measurement criteria.

Can you connect to the software we already use?

In most cases yes, via APIs, databases, exports or dedicated connectors. Before confirming it we analyse the tools and the access options available.

Does AI replace people?

Our goal is to remove repetitive tasks, manual searching and pointless steps. People remain essential for decisions, exceptions, relationships and control. How the work will change is assessed together with the team.

Can we start with a small project?

Yes, and it's often the best choice. One process, one measurable objective and a first version to put to the test. Then you decide whether to expand.

Does the system remain our property?

The contract clearly specifies ownership of the custom-built software, data, configurations, documentation and licences for any third-party technology. We design the solution to avoid unnecessary dependencies and to keep it transferable where technically possible.

Related gears

Where the path continues

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