Sensing intelligence group

Serious
insight.
Sensible
cost.

SYSENS pairs lean, easy-to-fit sensors with AI that reads the data and explains what it is seeing. Better information for the decisions you make, at a cost that is easy to justify.

Signal acquired
AI analysis
Guidance ready
01 / What we do

Three layers.
One clear picture.

Most monitoring stops at a dashboard of numbers. SYSENS goes further, taking raw data along with context, goals and expertise to provide AI-synthesised knowledge and guidance.

01 — Sense

Lean by design.

Compact sensor nodes built on proven components. They fit the equipment you already run, with no major install project and no heavy infrastructure, so the spend stays proportionate and the return is easy to see.

Proportionate costRetrofitBuilt on standards
02 — Analyse

AI that reads the data.

Our models learn what normal looks like for your engine, body, water or tank, then flag trends, anomalies and likely causes, with an honest level of confidence.

BaselinesAnomaly detectionConfidence
03 — Guide

Guidance that respects your expertise.

Findings arrive in plain language: what changed, why it may matter and the options worth considering. You know your engine, your body, your cellar. The call is always yours.

AlertsReportsOptions
See how the platform works →
02 / Divisions

Four domains.
One discipline.

Every field has its own physics, its own noise and its own decisions. Each SYSENS division shares one sensing-and-interpretation core, engineered for the realities of its domain.

04 / Proposition

Technology should not only report that something changed. It should help explain why it matters.

We make sophisticated sensing intelligible and useful for vessel owners, athletes, maritime operators and winemakers alike.

05 / Work with us

Let's find
the next signal.

Pilots, product partnerships, technical collaboration or distribution: start a conversation with SYSENS.

Contact

Prefer to write first? Email us directly. We reply personally.

SYSENS/CellarSense
Division 04 · Your personal winemaker assistant

Know where you are. Get where you want to be.

Tell us where you want to take your wines and your estate. We turn it into a clear, personal plan and help you make it happen.

Ask CellarSense ↗
How it works

Three steps, built around you.

01

Share your aspirations

A short guided interview about where you want to take your wines and your estate. A few strategic questions, never about your methods.

Start the interview →
02

Receive your personal plan

You'll receive a personalised document covering your goals, downloaded straight to your phone as PDF or Word.

03

Go in depth with AI

For an in-depth analysis, open CellarSense, your personal AI winemaker assistant. Explore your ideas, weigh your options and plan how to reach your goals.

Ask CellarSense ↗
What the interview gives you

Everything you tell us, organised and ready to use.

Your thoughts come back to you clear and structured, before you even open the assistant.

Your thoughts, organised

Everything you share, set out clearly in one place.

Personalised to your aspirations

Built around where you want to go, not a template.

Downloaded, and yours

It goes straight to your phone as PDF or Word. You keep it.

A head start with AI

CellarSense starts from your goals, so every answer is relevant to you.

Our approach

Your craft stays yours.

We may ask a few strategic questions about where you want to go. We never ask how you make your wine. Your methods stay entirely your own.

Begin here

Start with the interview.

Tell us your aspirations. We'll help you reach those goals.

Start the interview →
Platform · For investors and partners

One intelligence layer. Many domains.

Every SYSENS division runs on the same core. Sensors differ by domain, the AI underneath is shared, and what comes out is context written for that specific scenario.

Context examples are illustrative. A new domain adds its own sensors and context; the core stays the same.

01 / The opportunity

Sensors are everywhere.
Insight is not.

Hardware can now measure almost anything. Turning those signals into reliable insight is where most connected products stall.

Problem 01

Rebuilt every time

Each product team rebuilds the same data pipeline and machine-learning stack from scratch.

Problem 02

Learning stays local

Models learn device by device. What one installation discovers rarely benefits the next.

Problem 03

Locked in verticals

Systems that do learn at scale tend to be proprietary, expensive and tied to one industry.

02 / Data and trust

The learning is shared. The data stays yours.

Data ownership

Raw data stays with the customer. Shared models learn from patterns, not records.

Provenance by default

Every insight records its evidence and its confidence.

The call is yours

AI informs. People with domain expertise decide.

Open foundations

Open standards and open-source tooling. No lock-in.

03 / Why it scales

Every installation
sharpens the models.

New installations add evidence that improves existing models. New domains reuse the core, so each one costs less to launch than the last.

Phase 1 · Date TBC

Shared foundations

One data layer and shared memory serving all four divisions.

Phase 2 · Date TBC

Interpretation

From anomaly detection to explained findings, using history and context.

Phase 3 · Date TBC

Learning at scale

Shared models and governed updates across installations.

Phase 4 · Date TBC

Open platform

Partners bring their own sensors and domain expertise.

04 / Work with us

Let's find
the next signal.

Investment, grant funding, pilots or technical collaboration: start a conversation with SYSENS.

Contact

Prefer to write first? Email us directly. We reply personally.