AI agents in production, inside the systems you already use.

Typically between 6 and 16 weeks from discovery to go-live. This includes 1–2 weeks of assessment, 2–3 weeks of measurable proof-of-concept, then 4–12 weeks of development depending on integration complexity. Simple cases (e.g. email classification) take 4–6 weeks; integrations with enterprise CRMs or legacy systems need the upper end.

Realistic budgets for an Italian SME start at €15,000–30,000 for a simple agent (e.g. first-level customer service support), rise to €40,000–80,000 for agents integrated with the management software with document automation, and reach €100,000+ for enterprise projects with AI Act compliance. Operating LLM costs are typically €100–1,500 per month depending on interaction volume.

The AI agent is designed with automatic escalation: low-confidence cases are transferred immediately to a human operator. All generated responses are logged for review, and continuous monitoring identifies error patterns to improve prompts. Final responsibility stays with the company; the AI agent does not replace functions where critical human judgment is required.

No. Our approach is exactly the opposite: we integrate AI into your existing management software (TeamSystem, Zucchetti, custom) as an additional layer, without touching the core. AI features run in separate microservices that talk to the management software over APIs, reducing the risk of breakage and preserving your existing investment.

We measure ROI with concrete metrics agreed before go-live: average response time (e.g. from 4 hours to 30 seconds), automation rate (e.g. 65% of requests handled without human intervention), reduction of operator workload (e.g. 30% of human time freed), cost per interaction. A well-built AI agent typically repays the initial investment in 6–12 months.

Yes. We work with providers (OpenAI, Anthropic, Mistral) that offer enterprise options without training on customer data, or with on-premise / private cloud models when data sensitivity requires it. We implement encryption at-rest and in-transit, structured audit logs, and per-customer data segregation. Your DPO participates in data architecture decisions.

Yes. We implement the technical requirements of the AI Act: transparency (users aware they are interacting with AI), decision log (logging of critical inferences), bias avoidance (testing on representative datasets), human oversight (guaranteed human escalation), audit trail (all outputs traceable). Overall organizational compliance remains the client's responsibility; we deliver the software that makes it sustainable.