AI Solutions: AI agents and business process automation

Artificial intelligence is no longer a future promise: in Italy the AI market grew from 380 million euros in 2021 to 700 million in 2023, nearly doubling in two years. But between the slides of a demo and a system that genuinely saves hours of work every week there is an enormous difference. It is in that difference that we work.

At Digital-Enterprise we design AI solutions tailored to your real process, not generic packages. We start from an activity that costs you time or margins — a customer service team buried under repetitive requests, a team copying data between management systems, a document archive in which no one can find anything — and we turn it into an AI agent or an automation that works inside the tools you already use. No "revolution" that forces you to redo everything: intelligent integration on what you already have.

This has been our craft for over ten years: our CEO Vincenzo Lorusso combines software development and AI, and we use artificial intelligence in our own products too — such as SmartSafe, where GenAI generates the safety documentation for construction sites (POS/PSC). We know what holds up in production and what remains just a nice demo.

What we build: AI agents, automations and applied GenAI

We don't sell "AI" in the abstract. We build tools that perform a measurable task. The five areas in which we operate:

• AI agents and business process automation — flows that read, decide and act on your behalf: they route emails and tickets, fill in and move data between software, generate quotes or reports, trigger actions when a condition occurs. The goal is to take low-value, repetitive work out of people's hands.
• Intelligent chatbots and virtual assistants — assistants that answer customers 24/7 on the website, on WhatsApp or in internal channels, based on your content and not on invented answers, with handover to a human operator when needed.
• GenAI for content — assisted generation of texts, product descriptions, drafts and visual materials, in your tone of voice and under editorial control. Speed without losing the human touch.
• RAG and corporate knowledge bases — the model answers by reading your real documents (manuals, contracts, procedures, price lists), so the answers are grounded in your sources and citable. It is the technique that drastically reduces "hallucinations".
• AI integrations into your software — we bring AI into existing CRMs, management systems, eCommerce, apps and portals via API, without forcing you to change ecosystems.

How we work: from use case to system in production

We are wary of AI projects that start from technology. We start from the return: which activity do we want to automate, and how much does it cost today in time or in errors?

1. Discovery & use case — we analyze a concrete process, measure its cost and volumes, and define what "success" means in numbers (hours saved, response times, error rate).
2. Proof of concept — we quickly build a prototype on your real case to validate feasibility and quality before investing in the entire project.
3. Development & integration — we connect the AI to your data and your software, taking care of security, access management and GDPR compliance of data processing.
4. Testing, fine-tuning and human-in-the-loop — we verify the answers, define the cases in which the agent must stop and hand over to a person, and refine prompts and sources.
5. Release & evolution — we monitor performance in real use and improve over time. An AI system is not "delivered and done": it is trained.

Total transparency about what the model does, on which data and with which limits. No black boxes.

Who it is for (and who it is not)

AI solutions make sense when there is volume or repetitiveness. We typically work well with:

• SMEs and structured companies that have high-volume repetitive processes (support, back-office, data entry, quoting).
• eCommerce and retail that want sales assistants, automatic support and product-sheet generation on large catalogs.
• Firms and companies with extensive documentation (technical, legal, regulatory) that need to query it in natural language via RAG.
• Software houses and product teams that want to add AI features to their management system or SaaS.

We are also honest about the opposite: if a process is rare, highly variable or always requires critical human judgment, automation often isn't worth it — and we tell you that beforehand, not afterward.

Deliverables and concrete benefits

At the end of an AI project we don't leave you with a slide, but with something that works:

• An operational agent or automation, integrated into your tools and documented.
• A chatbot/assistant trained on your content, with a conversations dashboard.
• A queryable knowledge base with answers grounded in your sources (RAG).
• API integrations with existing CRMs, management systems and eCommerce.
• Technical documentation, access/permission management and GDPR-compliant configuration.

The benefit is measured where it counts: fewer hours wasted on repetitive activities, faster response times to customers, fewer transcription errors, corporate knowledge finally accessible, and team members free to focus on high-value work.

Pricing and how to get started

Every AI solution is tailored, so there is no single price list: the cost depends on the complexity of the process, the number of integrations and the volume of data. That is why we don't throw out random figures and don't lock you into rigid packages.

The fastest, lowest-risk way to understand whether AI is right for you is to start from a single use case with a proof of concept: contained investment, verifiable result within a few weeks, an informed decision on how to proceed.

To get started we just need to understand which activity weighs on you the most. Tell us about it in a free introductory call: we'll tell you frankly whether it makes sense to automate it, how, and with what order of magnitude of investment.