Privacy-safe scenarios, built from real patterns

Privacy note: to protect clients, we don’t publish names or confidential data. Each case is a realistic scenario based on real delivery patterns and outcomes.

AI that ships.
AI that sticks.

Below are concrete scenarios that show what changes when AI and automation are integrated into daily operations: less manual work, fewer errors, faster decisions, and a team that actually adopts the system.

Focus: ROI-first delivery
Domains: Finance, Operations, Professional Services
Approach: Secure, pragmatic, measurable
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Case Study 01

Vertex AI Knowledge Agent for a small business (Mantova, Italy)

A secure internal agent trained on ~25,000 documents—turning company history into answers, quotes, and decision support.
Problem: scattered knowledge Data: PDFs, emails, accounting exports Timeframe: 2009 → today
What changed: it feels like having an ultra-competent employee who remembers everything. Staff can retrieve accounting context from 2009 and generate quotes in seconds—without hunting through folders.
What we built
  • A private AI agent on Google Vertex AI, trained on ~25,000 internal documents
  • Retrieval + structured knowledge layer (accounting history, clients, suppliers, pricing patterns)
  • Role-based access + audit-friendly interaction design
  • Quote drafting: “based on similar jobs 2018–2024” → draft + references in seconds
Case Study 02

Invoice registration automation (Reggio Emilia, Italy)

Scripts + AI extraction to remove the monthly bottleneck and keep accounting workflows clean.
Problem: manual entry Risk: errors + delays Goal: exception-only review
What changed: the bottleneck disappeared. Instead of “typing and fixing”, the team reviews only exceptions and anomalies.
What we built
  • Invoice intake (email/folder/upload) → standardized processing pipeline
  • AI-based field extraction (supplier, dates, totals, VAT, line items)
  • Validation rules (duplicates, mismatches, missing references, anomalies)
  • Export into the existing accounting workflow (no tool overhaul)
Case Study 03

Commercialista: a client assistant that prepares the work

An internal assistant that classifies documents, flags what’s missing, and drafts client-ready summaries—so the accountant stays focused on judgment.
Problem: repetitive requests Peak season: chaos Need: consistent summaries
What changed: the studio operates like a premium firm. Faster turnaround, clearer communication, fewer “missing document” loops.
What we built
  • Document classification (invoices, expenses, contracts, bank statements)
  • Missing-items detection + reminders based on client profile
  • One-click “client situation” summary (reviewed by the accountant)
  • Risk and anomaly highlights (outliers, inconsistencies, deadlines)
Case Study 04

Avvocato: contract review & case prep copilot

A legal copilot that extracts clauses, flags risks, builds timelines, and drafts first versions—always with human review.
Problem: long documents Risk: missed details Goal: faster analysis
What changed: less time spent searching and formatting. More time on strategy, negotiation, and client-facing work.
What we built
  • Clause extraction (termination, liability, penalties, payment terms)
  • Risk flags for non-standard clauses and missing protections
  • Timeline generation from emails + PDFs (events, deadlines, attachments)
  • First-draft support for client updates (reviewed by the lawyer)
Case Study 05

An autonomous AI agent that runs in an isolated environment (privacy-safe)

A general-purpose agent workflow designed for total control: it operates inside a sandboxed environment, follows guardrails, and can execute end‑to‑end tasks across projects.
Problem: scattered execution Need: autonomy + oversight Constraint: privacy-first
What changed: work moves forward even when humans are busy. The agent takes briefs, produces structured plans, makes safe file edits, runs checks, and reports back—while staying inside defined boundaries.
What we built
  • An isolated execution environment (sandbox) with controlled access to files, tools, and network
  • Guardrails: allowed actions, approval points for sensitive steps, and recoverable operations
  • Project memory to retain decisions and context across weeks (without exposing identities)
  • A repeatable delivery loop: brief → draft → implement → verify → document → follow-up

Want outcomes like these in your business?

Send us one workflow you’d love to make faster (quotes, invoices, client onboarding, internal knowledge). We’ll reply with a clear plan: what to automate, what to leave manual, and how to measure ROI.

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No pressure. No jargon. Just a practical roadmap.