Your factory runs on data.
Now make it run on Intelligence.
Industrial machine learning built for the shop floor, not a data-science team. Detect anomalies, cut downtime and explain your OEE, connected to your machines, sensors, CSV or API in 48 hours.
Only 2.4% of factories have reached
real AI maturity. And the gap is widening.
The technology works. It just wasn’t built for the floor. Industrial AI has been sold as all-in-one platforms, with year-long integrations and a data-science team to run them, which reaches the top 1% and skips the other 99% of plants. Jemba is built for the 99%, reusing the data you already generate with no plant overhaul.
Source: OSS Ventures, “The Industrial AI Gap” — 914 on-site factory diagnostics.
Every tool hands you a model.
Jemba hands you the answer.
Most platforms stop at a model and leave the hard parts to a data scientist you don’t have. Jemba automates the whole workflow, so a process engineer gets a ranked, ready-to-act recommendation in the operator’s language.
718 variables.
10 that actually matter.
Instead of one more dashboard, Jemba ranks your process parameters by real impact on scrap and hands you a recommendation you can apply, straight through OPC-UA.
- Variable importance by SHAP, not guesswork.
- An optimal band 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 floor.
Plugged into your stack.
Jemba sits on top of the systems you already run and turns raw signals into ranked, ready-to-apply actions, from availability to energy, without forcing your plants to be identical.
- Model-expected vs. actual energy, with recoverable waste surfaced.
- Agent actions with an estimated €/yr and effort level.
- Apply through OPC-UA, PLC or a work order, no rip-and-replace.
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 to deploy.
Quality correlation
Find the root cause of defects in minutes by isolating the few parameters that truly drive quality among hundreds.
Energy monitoring
Model consumption against output to expose waste and turn energy from a fixed cost into a controllable one.
OEE optimisation
Don’t just measure OEE, understand it. Jemba surfaces the why behind performance losses, on the TeepTrak feed.
From raw factory data to ROI,
in four steps.
Connect your data
Stream from TeepTrak, upload a CSV, or push through the API.
Define the goal
Pick a target variable, algorithm and parameters, no code.
Let Jemba learn
Models auto-train; real-time predictions start immediately.
Act on the insight
Clear dashboards, ranked recommendations, tracked ROI.
Trusted on the floor by 450+ factories.
Jemba comes from TeepTrak — the production-monitoring platform manufacturers already run on the floor, proven in 30+ countries.
From 30% to 80% yield
across 12 production lines.
A global Tier-1 automotive supplier used Jemba to correlate 700+ process variables down to the 4 critical parameters driving 83% of yield losses.
Read the full case study ›What operators actually say.
“We ran the data through our usual Six Sigma tools to understand the process, and Jemba confirmed our analysis with a broader, faster view. Excellent work.”
“Jemba flags drift in our critical parameters well before operators notice. In three months, unplanned stops on our assembly lines dropped 34%. The model practically maintains itself.”
“What convinced me is we didn’t need to hire a data scientist. Our process team had it running in two weeks, and the first models were already live. That was the real test.”
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.
