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AI Service

Artificial
intelligence.

Where the system becomes autonomous

Chatbots, document classification, automated workflows, cross-platform integrations. Not AI because everyone does it - AI that returns real hours every week to the operations team.

The problem

AI is everywhere. Results are not.

80%
of AI projects fail - double the rate of traditional IT projects (RAND Corporation, 2024)
30%
of GenAI projects abandoned after proof of concept by 2025 (Gartner, July 2024)

The pattern is always the same: a vendor promises 'transformative AI', the tech team builds a pilot, nobody asks how to integrate it into real processes. Six months later, the project is on a digital shelf and the budget is spent. We start from the operational problem, not the technology. If AI doesn't return hours or money, we don't implement it.

What we do

End-to-end AI & Automation

We don't sell 'AI'. We build intelligent systems that integrate into your processes and deliver measurable value.

Conversational

Conversational AI

Chatbots, voice assistants and AI concierge that answer your customers 24/7 with the tone and precision of your best team.

Documents

Document Intelligence

Automatic classification, structured data extraction, advanced OCR and contract analysis. We turn piles of PDFs into actionable data.

Workflow

Workflow Automation

Automation on n8n, Make or custom Node.js pipelines. We connect your tools and eliminate every repetitive manual operation.

Predictive

Predictive Analytics

Forecasting, churn prediction, lead scoring and anomaly detection. We anticipate problems before they become costs.

Integration

Data Integration

API orchestration, ETL pipelines and real-time synchronization across platforms. Your data flows where it's needed, when it's needed.

Custom AI

Custom AI Solutions

Fine-tuning, RAG with company knowledge base, autonomous AI agents and custom solutions for use cases no off-the-shelf tool can solve.

How we do it

Technical approach and standards

Every project is built on solid foundations. No shortcuts, only engineering.

Tech Stack

OpenAIAnthropic ClaudeLangChainn8nMakePythonAWS SageMakerPineconeWeaviate

Standards

GDPR CompliantEU AI Act ReadySOC 2 ReadyOWASP Top 10

Integrations

SlackHubSpotSalesforceSAPZapierGoogle WorkspaceMicrosoft 365Notion
Our principles

Responsible AI, concrete results

Four non-negotiable principles that guide every AI project we build.

01

Data-first

We don't start from AI, we start from your data. If the data isn't there or isn't ready, we help you build the foundations first.

02

Human-in-the-loop

AI amplifies human decisions, it doesn't replace them. Every critical system includes supervision, fallback and manual overrides.

03

Measurable ROI

If it doesn't return hours or money to the operations team, we don't implement it. We define KPIs before writing a single line of code.

04

Privacy by design

Encrypted data, on-premise options, no training on client data. GDPR compliant and ready for the European AI Act.

For whom

The ideal client

AI works when there's a clear operational problem. We work with those ready to measure results.

Operations-heavy

Companies with repetitive manual processes: data entry, document classification, reporting. Hours lost every week that automation can return.

Document automation
Workflow orchestration
Data pipeline automation

Customer Service

Teams with high ticket volumes, response times to reduce and repetitive FAQs. AI handles the first level, the team focuses on complex cases.

Chatbot & voice assistant
Intelligent ticket routing
AI-powered knowledge base

Data-Driven

Companies that collect data but don't leverage it. Scattered Excel sheets, no automated insights, decisions by intuition instead of data.

Predictive analytics
Anomaly detection
Automated reporting

Enterprise Legacy

Organizations with established systems that want to integrate AI without rewriting everything. Incremental modernization, not revolution.

API layer & AI middleware
Gradual AI adoption
Compliance & governance
The numbers

Service KPIs

-20h
Ore Risparmiate / Settimana
< 2s
Avg Latency
> 96%
Classification Accuracy
3 mesi
Payback Period
-40%
Costi Operativi
99.9%
Uptime Pipeline
FAQ

Frequently Asked Questions

The answers you need, straight to the point.

AI delivers measurable value when your team spends significant time on repetitive, rule-based tasks: data entry, document classification, customer inquiry routing or report generation. We start with a Process Audit that maps your operational workflows, quantifies time spent on each activity and identifies where AI can reduce manual effort by 40% or more. The result is a prioritized roadmap with projected ROI for each automation, so you invest only where the numbers make sense.

A first functional AI module typically goes live within 4 to 8 weeks from kickoff. Simple automations like email classification or FAQ chatbots ship in the lower range, while complex pipelines involving document extraction, multi-model orchestration or ERP integration require the full timeline. Every project follows an iterative approach: deploy a working prototype fast, measure accuracy against real data, then refine until performance targets are met.

Yes, when implemented correctly your data remains fully protected. We deploy AI through enterprise API agreements that guarantee zero data retention by the model provider. For maximum control we configure private instances on your own AWS infrastructure, implement end-to-end encryption and enforce role-based access at every layer. All solutions comply with GDPR requirements, and we provide complete documentation of data flows for your compliance team.

Yes, an AI chatbot integrates natively with your website, CRM, helpdesk and internal tools through APIs and webhook connections. We build chatbots on LangChain that connect to HubSpot, Salesforce, Zendesk, Intercom and custom databases simultaneously. The chatbot accesses your knowledge base in real time, qualifies leads according to your scoring criteria and logs every interaction directly into your CRM with zero manual effort.

Simple automation follows fixed rules: if a condition is met, execute an action. AI adds the ability to interpret unstructured data, recognize patterns and make probabilistic decisions. For example, automation can route an email based on the sender address, while AI reads the email content, classifies intent, extracts key information and drafts a contextual response. We combine both layers through n8n orchestration and LLM integration to build intelligent workflows that handle the exceptions traditional automation cannot.

Ready to make your system autonomous?

We work best with companies that have a clear operational problem, data to build on and stakeholders ready to measure results. Let's discuss your use case.

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