Who We Are

We Don't Just Advise.
We Build.

Most consultants hand you a strategy deck. We hand you a running system, integrated into your infrastructure, used by real people, producing measurable results — with your team trained to own it after we leave.

That's the difference between advisory and execution. We're the second kind.

25+
Years of enterprise technology and systems integration experience
€1B+
Value of enterprise systems managed and integrated across engagements
1000+
AI tools and platforms evaluated and mapped in our curated directory
4 – 6
Weeks from discovery call to a live, production-ready AI system
Operators, not advisors

We've Run the Systems
You're Trying to Automate

The gap between AI strategy and AI production is an execution gap. We close it because we've been on both sides — as the system operators and as the builders of the systems that replaced manual work.

01
ERP & Enterprise Systems

Deep hands-on experience with Oracle, SAP, NetSuite, and bespoke ERP environments. We understand how enterprise data flows between systems, where it degrades, and how to build AI that connects to — and survives in — complex integration landscapes without creating technical debt.

02
System Integration Architecture

We've designed data pipelines at scale — connecting ERP, CRM, data warehouses, and cloud platforms across organisations with hundreds of users. AI systems that can't survive real enterprise integration environments never go live. Ours do.

03
Sales & Revenue Operations

We've operated and optimised commercial pipelines — CRM implementation, lead scoring, forecasting, sales process design. AI tools we build for revenue functions are designed by people who've run those functions, not just modelled them from the outside.

04
eCommerce & Digital Operations

Platform experience across Shopify, Magento, WooCommerce and custom storefronts — from architecture to fulfilment automation. AI for eCommerce we build is grounded in the operational reality of managing inventory, orders, and customer data at scale.

05
Workflow & Process Automation

Extensive implementation experience with Celigo, n8n, Talend, Zapier and Make — building and maintaining multi-system automation workflows in production. We don't just know how these platforms work in demos; we've debugged them at 2am when they broke in production.

Why it matters

Most AI consultants have never run the systems they're automating. They know how large language models work. They don't know how a NetSuite integration breaks at month-end, or why a CRM pipeline hasn't updated in 48 hours.

The consequence is AI systems that work in staging and fail in production — because they were built without operational context. Our team has the scars. That's what makes our builds different.

Platforms & systems we know in production

Oracle NetSuite SAP HubSpot Salesforce Shopify n8n Make Celigo AWS GCP BigQuery PostgreSQL OpenAI Anthropic LangChain Mistral Google ADK CrewAI LLamaIndex ...
How we work

Four Principles
That Govern Every Engagement

Principle 01

Speed as a discipline, not a feature.

We compress time deliberately. Not because we cut corners, but because we've designed a methodology that eliminates the delays that slow most implementations: scope creep, stakeholder misalignment, infrastructure surprises, and endless discovery phases that produce documents instead of software. Four to six weeks isn't a promise — it's a process.

Principle 02

One use case, built right, beats three built fast.

We resist the temptation to expand scope mid-sprint. A single production-ready system that your team actually uses generates more organisational value than three half-built prototypes that never reach users. We're ruthlessly focused on the outcome we scoped together — and on making that outcome undeniable before we discuss what's next.

Principle 03

We transfer capability, not dependency.

Every sprint ends with your team trained and capable of owning what we built. We don't design systems that require us to maintain them — we design systems that your people understand, can extend, and can improve without us. Because the signal that a sprint succeeded isn't when we deliver the system. It's when we become unnecessary.

Principle 04

We share the risk, so we have skin in the game.

Our fees are structured around the KPIs we define together before the sprint starts. Not time. Not effort. Not project milestones. This aligns our incentives with yours at a structural level — and it changes how we make every build decision.

Read about the RaaS model →
Our methodology

How a Typical
Engagement Unfolds

No two engagements are identical — but the sequence is consistent.

You tell us about your business, your data, and the problem you're trying to solve. We ask pointed questions and give you an honest early assessment of whether AI is the right tool.

We evaluate your organisation across five dimensions: data quality and accessibility, leadership and change capacity, technical expertise and training requirements, infrastructure readiness, and budget reality. This produces a single prioritised use case — the one with the highest probability of measurable business impact given your actual constraints. We deliver this as a brief, not a 60-slide deck. You'll have everything you need to make a go/no-go decision in about 20 minutes of reading.

We define the KPIs that will determine success before writing a line of code. These are specific, measurable, and agreed by both sides. We define scope, confirm infrastructure access, identify the internal team members we'll work with, and agree the sprint timeline. This document is the contract — not in a legal sense, but in the sense that everything we build is evaluated against it. If scope expands, so does the brief. Nothing happens quietly.

We build. Fast, with weekly checkpoints, iterating on real feedback from real users against real data. By the end of the sprint, you have a system deployed to your production environment, tested, documented, integrated with your existing stack, and in active use. Not a prototype. Not a pilot that needs six more months before it's "real". A live AI system producing results against the KPIs we agreed.

Parallel to the build, we develop the training and change management programme that gets your team from "passive recipients of a new system" to "active users who know how to get value from it". Executive briefings, hands-on user training, and technical upskilling for the team members who'll maintain and extend the system. Our target is 80%+ active adoption within six months of go-live — and we build the programme to achieve it.

We measure KPI performance against the baselines we captured at the start. We build the governance frameworks your enterprise needs to run AI safely at scale — audit trails, human-in-the-loop controls, EU AI Act compliance architecture. And if the sprint results justify the next sprint, we plan it together based on what we learned. The organisations that get the most from AI build it iteratively — one validated use case at a time, compounding.

Our background

Built on
15 years of Trust

RAAS Impact isn't a company assembled for a pitch. We have worked together across multiple companies and transformation projects for over 15 years — as founders, employees, and collaborators.

We've seen what breaks in digital transformation, what actually gets adopted, and what doesn't survive contact with reality. This venture is the result of all of that.

Giovanni Fagherazzi profile image
Co-Founder · Commercial Strategy & AI Adoption

Giovanni Fagherazzi

I help companies turn the promise of AI into real, measurable business outcomes.

 

After 20+ years leading digital transformation, global sales, and eCommerce growth at scale — from founding startups to directing operations at Arduino — I founded RAAS Impact to deliver Results as a Service.

 

My focus: guiding sales, marketing, and logistics teams through practical AI adoption. No fluff, no hype — just tangible impact on pipeline, performance, and process automation.

 

What sets me apart is my “mani in pasta” mindset: I’ve built what I now advise on. From launching Amazon channels in 11 countries, scaling Shopify ecosystems, designing omnichannel sales architectures, to integrating logistics and BI tools — I know what works and how to make it work fast.

AI Adoption Global Sales & eCommerce Go-to-Market
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Lino Moretto profile image
Co-Founder · Tech & Project Management

Lino Moretto

I empower clients to execute successful in-house AI projects.

Drawing from over 20 years of expertise as Fractional innovation Manager, I love bridging diverse knowledge areas while fostering seamless collaboration among internal departments, external agencies, and providers.

I am deeply committed to steering organizational success by spearheading change management and strategic initiatives that enhance performance across all dimensions. With a proven ability to transform underperforming areas and seize growth opportunities, I excel in building high-performance teams by recruiting top talent and fostering professional development at every level.

My approach is characterized by a collaborative and engaging management style, strong negotiation skills, and a clear vision to preemptively address operational risks.

AI Implementation Technology Project Management
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Francesco Varuzza profile Image
Co-founder · Operations & Digital Commerce

Francesco Varuzza

I make sure AI systems don't just launch — they survive the complexity of real operations.


With 25+ years building and running digital commerce at scale — from co-founding a full-service eCommerce company to managing operations for brands like Missoni, Seven, and Cinelli — I know what happens between "go-live" and "it actually works." Payment flows that break silently. Platform migrations that stall because nobody mapped the dependencies. Teams that adopt a tool on paper but route around it in practice.


At RAAS Impact, I own the operational backbone: process design, cross-functional coordination, and the unglamorous work of making systems hold up under real-world load. My background spans SAP, NetSuite, Odoo, Shopify, and Magento — not as product demos, but as production environments I've been accountable for.


What I bring isn't a technology preference. It's the ability to look at an organisation's operations, identify where AI creates genuine leverage versus where it creates new failure points, and build the rollout so it sticks. I've led change management and process improvement across B2B, D2C, and omnichannel — and I've learned that the difference between transformation that works and transformation that doesn't is almost never the technology. It's the operations around it.

Operations & Process Design Digital Commerce Change Management
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Start with a free 30-minute call

We've run the systems
You're trying to fix.

Tell us what you're building, what's blocking you, and what a result looks like. In 30 minutes we'll tell you honestly whether we can help — and what that looks like in practice.

No upfront cost · Italy · Malta · Europe · English & Italian
Book Discovery Call → Discover our services →

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