Industrial machine learning,
without the complexity.
Two ML algorithms across four use cases — predictive maintenance, quality correlation, energy monitoring and OEE. Jemba runs the whole workflow, so a process engineer gets the answer, not a model to babysit. No data-science team required.
Every tool hands you a model.
Jemba hands you the answer.
The hard parts of industrial ML are the steps around the model — the ones that usually need a data scientist you don’t have. Jemba automates all of them, end to end, and returns a prioritized, apply-ready recommendation in the operator’s language.
718 variables.
10 that actually matter.
Instead of another dashboard, Jemba ranks your process parameters by their real impact on scrap and hands you an apply-ready recommendation — straight over OPC-UA.
- Variable importance by SHAP, not by hunch.
- An optimal range per parameter (e.g. crimp force 4.2–4.5 kN).
- A quantified gain before you act: scrap, yield, € / month.
One place to run the plant.
Wired into your stack.
Jemba sits on top of the systems you already run and turns raw signals into prioritized, apply-ready actions — from availability to energy — without forcing your plants to look alike.
- Actual vs. model energy, with the recoverable waste highlighted.
- Agent actions with an estimated €/year gain and effort level.
- Applied over OPC-UA, PLC or a work order — without replacing everything.
Two ML algorithms.
Four ways to win on the line.
Predictive maintenance
Learn each asset’s normal behaviour and flag anomalies before failure — in under 2 seconds, with no data scientist.
Quality correlation
Find the root cause of defects in minutes by isolating the few parameters that really drive quality.
Energy monitoring
Model consumption against production to expose waste and make energy controllable.
OEE optimisation
Don’t just measure OEE — understand it. Jemba reveals the why behind the losses, on top of the TeepTrak stream.
Built to fit the stack you already run.
Machines, sensors, CSV or API — legacy equipment included. Jemba reuses the data you already generate, with no plant overhaul.
From raw data to ROI,
in four steps.
Connect your data
Stream from TeepTrak, upload a CSV or use the API.
Set the target
Pick target variable, algorithm and parameters — no code.
Let Jemba learn
Models train themselves; predictions start right away.
Act on the insight
Clear dashboards, prioritized recommendations, tracked ROI.
Trusted on the floor by 450+ factories.
Jemba is built by TeepTrak — the production-monitoring platform manufacturers already run on the line, proven across 30+ countries.
Improving a line shouldn’t wait for next year’s budget.
Book a 15-minute demo or start a free trial. 48-hour setup, no data scientist required.
Frequently asked questions
What is Jemba?
Jemba is an industrial machine-learning platform built by TEEPTRAK. It runs two proven algorithms — anomaly detection and correlation analysis — on your production data to improve maintenance, quality, energy and OEE.
Do I need a data scientist to use Jemba?
No. Jemba is built for plant and process teams. It connects to your existing data and returns prioritized, apply-ready recommendations in plain language — no data science team required.
How long does Jemba take to install?
About 48 hours. Jemba connects to the sensors, PLCs and historians you already have, without ripping out your existing infrastructure.
What can Jemba analyze?
Up to 700+ variables across predictive maintenance, quality correlation, energy monitoring and OEE optimisation — all from a single platform.
How much does Jemba cost?
Jemba is designed to be affordable for mid-size manufacturers, not just large groups. Book a demo to get pricing tailored to your lines.
