Data & AI for machine and equipment makers

Your installed base, turned into service revenue.

For machine and equipment makers with 20 to 250 people and a service team. We join up your after-sales data so you can see which machines and customers make or lose you money. And if your machines already send data, we turn it into a predictive maintenance service your customers pay for.

Book an intro call See the two offers ↓
  • No data team needed
  • You own everything we build
  • English and French
Five different machines at customer sites send live data to a predictive model. One cooling unit raises an alert, a visit is planned, and it is sold as a predictive contract.

Ten years of data platforms and automation, delivered for

  • AT&T
  • Danske Bank
  • Enovos
  • Carrefour
  • Axa
  • Air France

Telecom · Banking · Energy · Retail · Insurance · Industrial IoT

Sound familiar?

You build great machines. The service side runs on spreadsheets.

A machine is sold once. Service, spare parts and contracts come back year after year, and that is the part of the business nobody can see clearly.

  • Nobody can say which customers are profitable on service
  • Interventions, parts and contracts live in different tools and Excel files
  • Your machines send data to a portal, but nobody turns it into money
  • Each manager has their own numbers, and they don't match
  • Customers ask for uptime commitments you can't price yet
  • No data team, and no time to hire one

Two offers

Start where your data is today.

No clear data on your machines yet? Start with 01. Machines already connected? Go straight to 02. Both begin with a short assessment: we look at your systems and your data, and you get a written plan, a scope and a price.

ERP, Excel files, service tickets, spare parts and contracts flow into one installed base, which shows the margin per customer.

01 Start here

Service data foundation

Know which machines and customers make you money.

For you if your service data sits in an ERP, a ticket tool and a lot of Excel, and nobody has a clear view of the installed base.

  • Your installed base in one place: every machine, where it runs, which customer, which contract
  • Interventions, spare parts and contracts joined up
  • Margin per machine, per customer and per contract
  • Dashboards your service manager opens every week
  • The foundation for predictive maintenance later
Assessment, then build Ask for a price →
A machine signal goes through AI with guardrails. It produces a warning, approved by the service team, sold as a service.

02 Already connected

From monitoring to prediction

Sell predictive maintenance to your customers.

For you if your machines already send data (remote monitoring, an IoT gateway, telemetry) but it isn't a service you sell yet.

  • Machine data cleaned and linked to your installed base
  • Failure warnings built from the signals you already collect
  • AI that explains each warning in plain language, with guardrails
  • Your service team approves before any customer sees an alert
  • Packaged as a contract tier you can price and sell
Assessment, then build Ask for a price →

How it works

One call. One assessment. Then we build.

Small steps you can see, in your language, with nothing hidden in a black box.

  1. Intro call

    What you make, what data you have, what you'd like to sell. If there's no fit, we say so.

  2. Assessment

    We look at your systems and your data. You get a written plan, a scope and a price.

  3. Build

    Built in short steps, with a demo every week, in English or French.

  4. Handover

    You own everything: accounts, code, dashboards and documentation.

Proof

The work behind the two offers.

One case for each offer, and one that shows the scale.

Offer 02 · Prediction

A Belgian compressor manufacturer

They wanted to sell predictive maintenance to their customers. Brian built the real-time telemetry pipeline: data out of the compressors, streamed, stored, and turned into dashboards and alerts.

  • Node-RED
  • Kafka
  • Elasticsearch
  • Kibana

2019 · Brian's work as a consultant, before VizionEdge
Read the case →

Offer 01 · Cost visibility

A Belgian e-commerce company

They wanted to see where the money was going. Their data pipelines were rebuilt on one Azure platform, website analytics were linked to their reporting, and marketing analytics and performance forecasting came out of one place.

  • Azure Data Factory
  • Databricks
  • Azure SQL
  • Power BI

2023 · VizionEdge client

Proof of scale

A tier-1 European bank

Nine reusable infrastructure patterns that application teams used on their own, under audit: 100% audit compliance, releases monthly to weekly, projected cloud spend down 22%.

  • AWS
  • Terraform
  • Kinesis
  • Glue
  • Flink

2025 · VizionEdge engagement, through an AWS partner
Read the case →

Who you work with

Brian Blessou, founder.

Ten years building data platforms and automation for AT&T, Danske Bank, Carrefour, Enovos and Axa, and a real-time telemetry pipeline for a compressor manufacturer.

Today Brian also runs an AI system in production for a marketplace client, checked by 360 automated evaluations and 13 guardrails. That is the discipline behind "AI with guardrails" in offer 02: the AI is tested before it talks to anyone.

You work with Brian directly, from the first call to the handover.

Experience
10 years, since 2016
Degree
MSc Computer Science, data · Telecom Nancy
Languages
French · English
Company
VizionEdge SARL, Luxembourg
Delivery
Fully remote

Let's talk

Tell us about your machines.

A short intro call: what you make, what data you have, what you'd like to sell. You'll leave knowing which offer fits, or that neither does.

Book an intro call WhatsApp: +352 661 491 929 brian.blessou@vizionedge.io

Brian Blessou · Founder · English and French

VizionEdge SARL · 19 rue de l'Industrie, L-8069 Bertrange, Luxembourg