jemin.ai
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Neural AI Digital Twins — Since 1988

Neural AI that models your world in fine detail, because everything is unique

Precise digital twins of real-world processes and behaviours — to detect anomalies, quantify uncertainty and answer questions conventional models can't. Every application on the right is a real dataset — press play to watch it worked end to end.

Two ways to put your data to work

Learn The Big Picture Or Learn On The Fly

Learn once from a dataset, or keep learning from a live stream — the same neural approach, refined since 1988.

NEURAL AI · BATCH MODELLING
Neural AI
Turn a spreadsheet into a predictive model. Forecasts and classifications with quantified uncertainty, self-explaining what-if and cross-sections, and one-click export to Excel, VBA and C++.
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ARENA AI · REAL-TIME
Arena AI
Point the AI at a live stream — markets, sensors, telemetry. It forecasts the next move, flags anomalies the instant a reading breaks pattern, and keeps improving online with every reading.
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01 — What we do

Four capabilities that set us apart

I
Small-data neural modelling
Algorithms refined over three decades extract robust insight from small, noisy, incomplete, inconsistent data. No big-data requirement, no heavy engineering.
II
Quantified uncertainty
Every twin ships with a twin of uncertainty — a triplet. It tells you what the model predicts and how confident it is, so you can triage.
III
Automated anomaly detection
The triplet defines the expected envelope. Readings outside it — by how much, with what confidence — are flagged and ranked automatically.
IV
Explainable reasoning
Models explain their outputs — quantifying each input's contribution and answering counterfactuals: change this by 10%, what happens?
03 — Why jemin.ai

Built for the real world, not the textbook

Most AI tools assume conditions that rarely exist outside a lab: large, clean, well-structured datasets. The real world is messier — and the gap between what AI promises and what it delivers is usually traced to exactly that mismatch.

jemin.ai was built from first principles to work with data as it is found. Our approach has been refined through real commercial deployments since 1988, across petrochemicals, pharmaceuticals, retail and finance. It doesn't need years of history, and it doesn't break down on gaps, noise or outliers.

The result reaches problems conventional AI cannot — with outputs that are accurate, defensible and explainable, and exportable as C++, VBA or Excel for integration.

1988
Research origins
290+
Worked examples
Triplet
Prediction · uncertainty · anomaly
C++ / XLS
Export for integration
04 — Applications

Where the technology has been applied

Predictive maintenance
Model the expected operating envelope; detect deviations before they become failures; reduce unplanned downtime.
Forensic accounting
Identify anomalous expense claims and records, ranked by confidence. Focus investigation where it matters.
Clinical trials
Quantify drug efficacy and uncertainty from small datasets; decide whether further trials are needed.
Risk analysis
Model contract and investment risk, quantifying return and uncertainty. Spot contracts riskier than they appear.
Time synchronisation
Data centres, telecoms and power grids: tokens-per-watt, edge time-error and localisation from timing data.
Price & demand
Model how sales respond to price, advertising and seasonality; find the profit-maximising price with confidence.
Arena AI · real-time

Real-time AI that learns as it runs

Where Neural AI learns from a fixed dataset, Arena AI learns from a live stream — forecasting one step ahead, flagging anomalies and adapting online, with no retraining runs.

I
Live forecasting
Predicts the next value of a stream — markets, sensors, telemetry — one step ahead, scored honestly on the very next reading.
II
Anticipation
Reads a leading indicator and acts before the error appears, instead of reacting after the fact.
III
Anomaly flags
Flags a reading the instant it breaks its learned pattern, with a live measure of how surprising it is.
IV
Online learning
Improves with every reading and adapts as conditions drift — warm-started from recent history, no retraining team.
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Get in touch

Every problem starts with a conversation

We work with a small number of clients at a time, so every engagement gets close, expert attention. Early conversations are always without obligation.