italian software house

We govern AI to build better software, in less time.

We are senior engineers who know how to use AI in every phase of the product lifecycle: more productivity, more quality. Scope, price and date are written before we start.

01: Experience10+ years
02: Engagements7 packages
03: Expertise7 technical areas
04: ApproachAI in every phase
how we use AI

Why, in our hands, AI changes the result

Having access to the tools is not enough: what counts is knowing how to govern them. It is an engineering skill, and we bring it to every package to get two things.

More productivity

  • Repetitive work, such as drafts, boilerplate, summaries and code searches, we do in a fraction of the time.
  • We know which tasks to hand to AI and which not, and how to give it context and constraints so the result is usable on the first pass.
  • The time saved shows in the delivery dates, which we declare before we start.

More quality

  • With more time for design and verification, the code is more polished and easier to read for whoever comes after us.
  • Tests are written before the changes and cover more cases, because generating them costs us less.
  • Every line that enters the product goes through review by a senior engineer: technical responsibility is ours.
lifecycle

AI, governed by us, in every phase of the product

Four phases, one scope written before we start. In each one we use AI as a tool: less time on repetitive work, more time on design, verification and quality.

Analysis: understand it well, faster

Interviews, tickets, requirements and existing code: scattered inputs that we put in order with AI, so the decision is made with the full picture.

How we use AI

  • We condense interviews, tickets and feedback into a structured brief
  • We have AI read code and APIs to see where to start looking
  • We prepare drafts of requirements and acceptance criteria, then refine them ourselves

How we check

One of our engineers verifies every finding before it reaches a report.

Related packages

Development: AI under our guidance, quality code

In the code we know how to steer AI: we give it the project's context, constraints and standards, and the first pass arrives much sooner. The result follows the same rules as any other change.

How we use AI

  • We write code and changes with AI, guided by the project's context and standards
  • We generate test cases from the system's current behaviour
  • We query documentation and code as a single knowledge base

How we check

Review and tests decide what goes in; tests pin the behaviour before any change.

Related packages

Release and publishing: small releases, written notes

Going live is where a mistake costs the most. With AI we take repetitive work off the path and keep control.

How we use AI

  • We prepare release notes and changelogs from the changes made
  • We compare what changes with what is documented, to find the mismatches
  • We write drafts of the content to be published, which we approve first

How we check

Every release stays small and reversible, and one of our engineers approves it.

It is not a priced package today: scope and deliverables are written together on a call, before we start.

Team: the state of the work, always readable

With several people on one project, the cost is in coordination. We use AI to keep it readable.

How we use AI

  • We summarise the state of tickets and progress for anyone who missed the thread
  • We keep documentation and decisions findable for whoever joins the project
  • We rebuild the context of a decision from sources already in place

How we check

Technical responsibility stays with CODEPRESS: we make the decisions.

It is not a priced package today: scope and deliverables are written together on a call, before we start.

packages

Engagements with a price and a date

No open-ended consulting billed by the day. Every engagement starts from a precise question and ends with something you can read, use or ship.

  1. understand

    API audit

    The APIs you expose to your clients, your partners or your own frontend, read the way whoever has to integrate with them would read them, or whoever wants to break in.

    €1,500 – €3,0002 weeks · fixed price
  2. understand

    Code audit

    The software you already run in production, looked at by people who could also fix it. No questionnaire to fill in.

    €1,500 – €3,0002 weeks · fixed price
  3. put right

    Targeted refactoring, backend or frontend

    Not a rewrite of the system: one bounded area that today slows down every change, put right without stopping the rest.

    from €6,0003–6 weeks
  4. build

    Feature development

    A feature your team has no time or no skill for right now, taken from analysis all the way to production.

    from €8,0004–10 weeks
  5. decide

    PoC in four weeks

    When the question is not how much it costs to build, but whether it works at all. A prototype is there to answer, not to impress.

    €4,000 – €8,0004 weeks · fixed price
  6. AI in your company

    Enterprise RAG, assistants and onboarding

    Our own framework: company documentation becomes a single library, served to three different audiences without duplicating it.

    from €6,000pilot · 4–6 weeks
  7. getting found

    A showcase site built to be found

    For sole traders and small businesses with no presence online: the site built and published by us, optimised for search engines and for AI assistants.

    from €4002–3 weeks · €100/year maintenance, optional
method

How we work

The method is the only thing a client can check before signing. Ours comes down to seven rules, and they hold on every package. With AI we work faster, but the rules stay the same.

The scope is written first

What is in, what is out, what we deliver and by when. If we cannot write it down we have not understood the problem: we go back to analysis instead of starting anyway.

Price agreed upfront, not tallied at the end

You know the cost before we start. If work outside the scope shows up we say so when it shows up, with a separate estimate: it does not turn up on an invoice at the end of the month.

Tests first, changes after

On code we did not write we start with characterisation tests: they pin down current behaviour, so a refactor that breaks something shows it the same day.

Small, reversible releases

No big-bang delivery after months of silence. Every step lands in an environment you can look at, and can be rolled back without an emergency meeting.

No rewrites out of habit

Rewriting from scratch is the most expensive and riskiest answer. We propose it only when we can show, with numbers, that it costs less than evolving what exists.

Every finding verified by hand

Automated tools flag a lot and are often wrong. What ends up in our reports has been looked at by a person: a padded report helps nobody decide.

Technical responsibility stays with us

We assemble the team around the project from our network of senior developers. Whatever its composition, that code is ours to answer for.

expertise

Technical expertise

  • Frontend
  • Backend
  • Database
  • Cloud & infrastructure
  • Testing & Quality Assurance
  • AI integration
  • Blockchain integration
faq

Frequently asked questions

How does a project with you start?

With a 20-minute technical call, no strings attached: we work out the problem you're facing and tell you straight away which of the seven packages covers it, or whether it needs clarifying first. If the package fits, you receive a written proposal with the scope defined, the price and the delivery date, ready to sign.

Are the published prices final?

For audits and the PoC, yes: the scope is fixed and so is the price, agreed before the work starts. For refactoring, feature development and AI work we publish the starting threshold instead, because the final cost depends on how wide a scope we agree on together.

Do you work remotely?

Yes, we work entirely remotely and don't offer an on-site option: we don't travel to a client's office, and we don't ask anyone to work from ours. We collaborate with companies in Italy and abroad, with no office or geographic constraints. The registered office listed in the site footer is a company-registry fact, not a place where any work actually happens.

Do you offer support after the release?

Yes. Every package can include maintenance, monitoring and evolution of the software after delivery: we don't disappear on release day. Software needs managing over time because the data, the traffic and the dependencies around it keep changing, not writing once and leaving it to run on its own. We talk about it at the end of each engagement, based on what's actually needed.

Do you also work on existing systems?

Yes. Most of our work starts from software that already exists, not from a blank page: we read it with an audit, secure it, evolve it with new features, or put it right with a targeted refactor, without unnecessary rewrites. The code you already have in production stays the starting point, not an obstacle to throw away and rebuild from zero.

What kind of contract do you work under?

Every package starts from a scope written down before we sign: what is in, what is out, what we deliver and by when. Price and date are agreed upfront, inside that scope, and don't change once work has started. If something outside the scope shows up while we work, we flag it when it happens, with a separate estimate: it never lands as a surprise line at delivery. That holds on every package, not just some.

Who owns the code you write?

Yours, whenever a package produces code: we don't retain rights over what we write, and being able to use it later never depends on keeping a contract with us running. Depending on the package, the code either lands straight in your own repository as we go, or we hand over the source at delivery: nothing we write stays accessible only by going through us. What stays ours is the technical responsibility for that code, not a claim over it.

Who actually works on the project?

Not two fixed developers who work every project: we assemble the team around the project, drawing on our network of senior developers, and the work decides the size, not an org chart set in advance. Whatever composition we choose, technical responsibility for that code stays with CODEPRESS, not with whoever happened to write it that day: that responsibility is what you're buying alongside the package, not a specific name pencilled into a calendar.

In which phases of the work do you use AI?

In all of them: from analysis to development, from release to team coordination. We use it where it removes repetitive work without removing control, for example to condense scattered inputs, write code and tests or draft release notes. Where we use it and where we don't is written into the scope, before we start.

Who is responsible for code written with the help of AI?

We are. AI is a tool and our engineers are the ones governing it: what it produces goes through review and tests like any other change, and no finding enters a report or a release without a person having checked it. Technical responsibility stays with CODEPRESS, whatever tool was used to write that code.

Can I add AI to my product without rewriting it?

It depends on the system, but often yes: an AI feature plugs into what you already have, without rewriting it. We know how to integrate it and how to govern it: it starts from a single measurable use case, with a pilot, and at the end you know whether it holds up on your process before extending it. If the case is about your documentation, the starting point is the enterprise RAG package.

Have a project in mind?

Tell us about it in a free 20-minute technical call: we reply with a concrete proposal.

Book a call