Physical AI for continuous manufacturing

Catch process drift before it becomes cost.

ProcessMiner predicts quality every 30 seconds from the data your plants already collect, and shows your team exactly what to adjust.

Trusted on the floor at leading manufacturers

International Paper Smurfit Westrock Georgia-Pacific Graphic Packaging International Metsä Group Kruger
  • 10+ years, since 2015
  • 50+ plant deployments
  • 20+ major paper manufacturers
  • Pulp & paper, nonwovens, water

How it works

From reacting to the lab to acting ahead of it.

Variability is the most expensive line item your P&L doesn’t show. Your team knows the process. The problem is acting in time, when the lab reports 30 to 60 minutes after the product is made.

Reactive optimization

Act after the outcome

  • Drift begins.
  • The lab finds it.
  • The loss is booked.
Proactive optimization

Prevent before it happens

  • Predict. Quality predicted every 30 seconds, between lab tests. Learn more →
  • Pinpoint. The top 10 likely causes, ranked by influence. Learn more →
  • Correct. The exact adjustment back to your best run, or applied automatically within limits you set. Learn more →
Case study Paper manufacturing line
25%
Less chemistry
Reduced wet-strength dosage
23%
Reduced quality variation
Tighter, consistent quality
~$1M
Cumulative savings
12 months

Single-deployment results, measured against each plant's own baseline. Results vary. How we measure →

The ProcessMiner platform

Six ways the platform turns data into decisions

A live quality prediction, the ranked cause, the next setpoint, a plain-language answer and models your team builds, all from the process data you already collect.

01 / Every 30 seconds

Real-Time Prediction

Your lab reports what already happened. Real-Time Prediction shows your team where quality is heading every 30 seconds, between lab tests, with a recommended correction before product goes out of spec.

  • Recommendations at most every 15 minutes, only when the trend heads out of bounds
  • Grade/SKU transitions handled automatically, without reconfiguration
Explore Real-Time Prediction
02 / Find the cause, fast

Root Cause Analysis

When quality breaches its limits, Root Cause Analysis narrows hundreds of process variables to the top 10 likely causes, ranked by influence, so your engineers start from a short list, not a screen full of tags.

  • Ranks factors by deviation severity and importance
  • Filters out redundant, correlated signals
Explore Root Cause Analysis
03 / Your best run, live

PM Vector

PM Vector puts your best run on screen as a live target for the grade you're running. When a variable drifts, operators see the exact setpoint to move to, so your best crew's settings guide every crew.

  • Separates levers operators control from variables they can't
  • Targets update as equipment, feedstock and conditions change
Explore PM Vector
04 / Ask in plain language

PM AI Agent™

PM AI Agent answers production questions in plain language, using your live process data, root cause findings, SOPs and manuals. It cites its sources, so every shift has your best operator's judgment on call.

  • Answers from your plant's own data and documents, not the open internet
  • Runs inside your environment, with on-premises deployment available
Explore PM AI Agent
05 / Built by your team

PM Studio™

A no-code environment where your team uploads historical data, builds and reviews predictive models offline, then deploys them to a live dashboard in hours once your live data connection is in place. Models retrain on each new lab value.

  • Hundreds of modeling approaches tested; best fit chosen per machine and grade/SKU
  • No code or data-science team needed to build or review models
Explore PM Studio

06 · Autonomous Optimization

From recommendations to automation, at your pace.

Every deployment starts in open loop, with operators acting on recommendations. Move toward closed loop only when results earn it, and only for levers you choose.

  1. 01Open loopOperators act on recommendations.Every deployment starts here
  2. 02Hourly sprintsShort autonomous runs, with an operator on watch.
  3. 03Extended runsSprints across full shifts.
  4. 04Closed loopFully autonomous, within limits you set.
RecommendationsAutomation

At each step, a value capture report measures quality, throughput and waste against your baseline. Explore Autonomous Optimization

What it improves

Better quality, more throughput, less waste.

Quality

Product held in spec, shift after shift.

>20%
Less quality variability · Pulp & paper deployments

Throughput

Drift corrected before it becomes a stop.

$20K–$200K
Cost of one hour of downtime · Industry benchmark

Raw material & energy

Less chemistry, fiber and energy added as insurance.

Up to 25%
Less chemistry · Pulp & paper deployments

See what your plant looks like when every shift runs like the best one.

  1. 1Pick a problemThe quality, cost or throughput problem that matters most to you.
  2. 2Data Health AssessmentWe take a closer look at your process data, at no cost.
  3. 3FindingsWe let you know exactly what your own data can do.
  4. 4PilotOne site, one defined problem, measured against your baseline.
  5. 5DeploymentAcross lines and sites, on an agreed timeline.

Start with a free Data Health Assessment. We’ll take a closer look and let you know exactly what your own data can do.

Already sure? Ask about a pilot.

Questions, answered

Frequently asked questions

What does ProcessMiner do?
ProcessMiner is a Physical AI platform for continuous manufacturing, running today in pulp & paper, nonwovens and water. It connects read-only to the data your plants already collect, predicts quality between lab tests, ranks the variables driving a deviation and recommends the set point to move to, so product stays in spec. The result is better quality, more throughput and less material waste, with operators in control.
How do we know the results are real?
Every result we publish is measured against that plant’s own baseline, with a measurement approach agreed in advance and reported month by month, not against an industry average or a vendor benchmark. See how results are measured →
What does the Data Health Assessment produce?
We take a closer look at your process data, show which metrics have room to improve, and let you know exactly what your own data can do. It’s free. It doesn’t produce a dollar figure: you put the value on it with your own costs. We need 6–12 months of process history for the asset, with lab results that carry a timestamp (LIMS, spreadsheets or paper logs all work).
How is it priced?
We don’t quote pricing over email or on the site, because it depends on your process and scope. The free Data Health Assessment and the first pilot conversation are both no-commitment — get in touch and we’ll talk specifics.

Get in touch

Have a question?

Whether it's our platform, your process, or a free Data Health Assessment you'd like to start, let us know.

This field is for validation purposes and should be left unchanged.