AI for manufacturing that respects your existing lines.
Real-time intelligence on the factory floor · without ripping out what works.
Manufacturing AI fails when it asks the factory to change. The lines run on PLCs from three different decades, the ERP is older than most of the engineers, and the night shift cannot wait while a model retrains. We build for the factory you actually have, not the brochure.
We connect the cameras, sensors, and old machines that already exist · seven systems that never talked to each other become one clean real-time pipeline. The AI watches every frame, listens to every vibration, and alerts the floor team in milliseconds when something needs attention.
From vision-based defect detection to predictive maintenance and yield optimization, the wins are measurable: defects caught earlier, downtime avoided, chargebacks prevented.
Four places to start.
Each of these has shipped in production for a real manufacturing customer. Pick the closest match to your situation.
Vision-based defect detection
Cameras on the line watch every product. The model flags defects the human eye misses · and explains why each one was flagged so the QA team can train it.
Predictive maintenance
Vibration, temperature, and current signals feed a model that predicts bearing, motor, and tooling failures hours before they happen. The maintenance team moves from reactive to scheduled.
Yield and throughput optimization
Find the recipe and timing combinations that produce the most good output per hour. Often a 2–4% throughput improvement is sitting inside the data you already have.
Operator copilots
Voice and screen assistants on the floor that answer "what changed" and "what should I do" without the operator leaving the station.
Three steps. No surprises.
The same shape as every Fornext engagement · from manufacturing to banking to restaurants. You see real progress in weeks, not quarters.
Connect what is already there
We start with a 2-week instrumentation sprint: pull data from the PLCs, cameras, ERPs, and sensors that exist today. No rip-and-replace.
Train on your real defects
Real defect images, real downtime events, real yield data. Not synthetic data. The model learns the failure modes your line actually produces.
Shadow mode, then go live
Every model runs in shadow mode for at least two weeks before it triggers any action. Your team sees what it would do, signs off, then it goes live with rollback always one click away.
The questions manufacturing leaders ask us.
These come up on every manufacturing discovery call. The answers are real, not sales-deck answers.
Have a different question? Ask usWill this work with our old PLCs and machines?
Yes. We have integrated Allen-Bradley, Siemens, Mitsubishi, and several legacy PLCs that predate current networking standards. Where a machine has no digital output, we add a small industrial sensor and read it ourselves.
How long does installation disrupt the line?
Most installations run during planned maintenance windows. The vision systems are non-invasive · we mount cameras, not modify the line. The first connected dashboard is typically live within two weeks.
What if the model makes a bad call?
Every prediction is reversible. The system suggests; the human confirms. We also keep a one-click rollback to the previous model version · if a release goes sideways, your team can revert in seconds.
Can we own the model and data afterwards?
Yes. You own the model weights, the training data, the labels, and the documentation. If you decide to leave us, the system leaves with you.
AI that earns the trust of clinicians, regulators, and patients.
AI that reads like a careful junior associate · without crossing matters.
Real-time decisions · with explanations regulators accept.
Voice agents that pick up the phone · in any language, 24/7.
Talk to us about your manufacturing project.
One short call. We'll tell you what we'd do, what it would take, and what it would cost · even if we end up pointing you somewhere else.