Reduce quality variability
See quality drift as it starts, not after the lab confirms it. Hold the process closer to target, run after run, so quality stays consistent instead of swinging between the guardrails.
Trusted on the floor at leading manufacturers
The challenge
You know your process.
The problem is acting on it in time.
Most plants sit on massive amounts of process data they can't turn into action fast enough. Your team already knows how the line behaves — what's missing is data that moves as fast as they do.
Optimize for what matters
Improve quality, cut chemistry and energy waste, and lift throughput — the outcomes that show up on the bottom line. ProcessMiner turns your process data into the specific moves that get you there.
Built on your team's expertise
You know your equipment and your product. ProcessMiner brings the process intelligence and puts it directly in your operators' hands — no coding, no rip-and-replace. Speed to value, built on the knowledge your team already has.
The ProcessMiner difference
Reactive vs. proactive process
In the reactive model, the line keeps running while quality deviations are handled after the fact, and operators wait for lab results to confirm what happened before they can act. In the proactive model, ProcessMiner predicts the trend in advance so the deviation is corrected with a recommendation or automation, and quality holds in target the whole time.
Reactive optimization
Act after the outcome
Operators react only once waste has already happened.
- Drift begins. The process quietly trends toward the spec limit, unseen.
- Quality escape recorded. A lab result or scrap reveals the deviation after the fact, while the line keeps running.
- Late manual fix. The operator reacts, but the loss is already booked.
Proactive optimization
Prevent before it happens
ProcessMiner predicts the trend and corrects in real time.
- Trend predicted. The model predicts the quality deviation before it reaches spec.
- Correction applied. The operator is guided, or closed-loop control adjusts the setpoint live.
- Defect prevented. Quality holds in target: no scrap, no escape.
Case study Paper manufacturing line
25%
Less chemistry
Reduced wet-strength dosage
63%
Better target adherence
vs. operator baseline
23%
Reduced quality variation
Tighter, consistent quality
$1.5M
Cumulative savings
12 months
Results from a single ProcessMiner deployment measured over 12 months. Actual results vary by facility, process, and data quality; past performance is not a guarantee of future results.
The PM Studio advantage
Five ways the platform turns data into decisions
From your first upload of historical process data to live predictions, pinpointed root causes, and an AI assistant on the floor, without writing a line of code.
01 / No-code, built by your team
PM Studio
PM Studio puts optimization in the hands of the people who run your process. No-code tools test hundreds of approaches, from statistical methods to deep learning, and select the best fit for your equipment and product grades/SKUs. Once connected to your historian, operators go from raw process data to a live predictive model in minutes, catching quality issues in real time so you can act before waste happens.
- No-code model building: operators configure quality targets, process variables, and grade/SKU definitions themselves
- Hundreds of modeling approaches tested automatically; the best-performing model is selected per machine and grade/SKU
- Deploy in minutes once connected to your historian, no rip-and-replace
Built for the plant floor
02 / Live, every 30 seconds
Real-time quality prediction
Your lab takes 30–60 minutes to tell you where quality is heading; PM Studio updates the prediction every 30 seconds, across multiple parameters simultaneously, so your team knows what's coming before a quality deviation becomes a problem. Grade/SKU transitions are handled automatically as the active product changes.
- Built-in grade/SKU-transition logic adjusts the model as production shifts between products
- Manages a wide range of grades/SKUs without manual reconfiguration
Reactive vs. proactive
03 / Find the cause, fast
Proactive root cause analysis
When quality goes out of bounds, the platform narrows the field down to the 10–15 most likely causes, ranked by influence, not by guesswork. Engineers get a clear starting point, not a data dump.
- Ranks contributing factors by quality deviation severity and relative importance
- Filters redundant signals so your team acts on what actually matters
Top root causes
04 / The "golden run"
Intelligent Centerlining™
Every process has a best version of itself. Centerlining compares real-time production against your historical performance benchmarks and tells operators exactly how much to adjust specific controls (a precise amount, not a vague alert) to bring the process back on target.
- Distinguishes what operators can control from what they can't
- Quantified setpoint guidance: specific adjustments, not general warnings
Live vs. golden run
05 / On-demand AI assistant
PM AI Agent
An AI assistant purpose-built for the plant floor. PM AI Agent combines live process data, root cause findings, and your existing plant knowledge (SOPs, equipment manuals, downtime logs, etc) to answer production questions in plain language, instantly.
- Ask "what's driving this week's quality deviations?" and get a grounded, sourced answer
- Runs leading AI models over your data, on your terms, with no data leaving your environment
Example of an operator asking PM AI Agent about live production conditions, predicted limits, root causes, and plant documentation.
Simulated conversation. On your line, PM AI Agent answers from your live data, SOPs, and RCA findings.
Built vertical-agnostic
One platform. Any continuous process.
PM Studio doesn't come pre-loaded with industry rules. It builds from your process data: quality targets, historical runs, and the variables your operation actually tracks. That's why the same platform runs in pulp & paper mills, food and beverage plants, wastewater facilities, and nonwovens, and adapts to whatever comes next.
Connects to what you already have
No rip-and-replace. PM Studio connects to your existing process historian and data infrastructure, typically in under 30 minutes, regardless of manufacturer or system type.
Models built from your data, not our assumptions
Every model is built from your facility's own historical production data. No generic industry templates, no proprietary black box: the platform automatically fits itself to your process.
You define what matters
You set the quality targets, product grades/SKUs, and process boundaries. The platform conforms to your operation, not the other way around.
Root cause that works across any process
Root cause analysis ranks contributing factors independently, evaluating both linear and non-linear relationships across your process variables, regardless of industry or equipment type.
See it on your own data
Not ready for a pilot? Start with a Free Analysis.
Send us the historical process data you already collect. We'll build an offline PM Studio dashboard, run a data healthcheck, and review the findings with your team, no commitment required.
No coding required. Findings reviewed with your team before you decide on next steps.
Integration & flexibility
Fits your stack.
Earns your trust.
Connect to live data quickly, let the platform handle signal quality automatically, and move toward autonomous control only when you're ready.
Plug-and-play connectivity
Flexible connection options work with your existing data infrastructure. Most sites are connected and pulling live data in under 30 minutes.
Automated data cleaning
The platform handles missing, flat, or corrupted signals automatically. Your team spends time on decisions, not on preparing data.
Path to autonomous control
Start with advisory dashboards. As confidence builds, move to closed-loop control at your own pace. You decide which variables the system influences and when.
~30 min
to connect your historian
Hours
to a first live model
Under 2 weeks
to full deployment
Proof of scale & trust
"Our customers trust us because we're not just a software company — we're a pioneer in AI for manufacturing. That depth of operational expertise, paired with deep process intelligence, is what delivers bigger savings, better margins, and a real edge over the competition."
Karim Pourak, Co-Founder & CEO of ProcessMiner
50+
Enterprise deployments
High-variability environments
30s
Quality prediction cadence
Continuous, live
15min
Recommendation cadence
When action is needed
100%
Data confidentiality
Strict access & governance
Questions, answered
Frequently asked questions
How quickly can ProcessMiner be deployed and start showing value?
Full platform deployment typically takes under two weeks once historian connectivity is established. Connecting to your data historian can be set up in approximately 30 minutes, and from there live predictive models can be built in just 1 to 2 hours.
How does the platform connect to our live data?
It integrates securely with your existing historian through flexible options. Use direct API endpoints (like PI Web API) or a lightweight, on-premises Windows virtual machine agent.
What types of predictive models does PM Studio use?
PM Studio automatically builds and selects the best-performing model for your process, drawing on a broad range of statistical and machine-learning methods, no coding or manual tuning required.
How does the system choose the "best fit" model, and can we customize it?
The platform picks the best-fit model for your process automatically. If your domain experts have preferences for certain machines, grades/SKUs, or mills, the model-selection criteria are fully adjustable and can be customized to your needs.
Can the system handle frequent grade/SKU changes or product transitions?
Yes. The platform has built-in grade/SKU-transition logic that continuously adapts the model based on the active grade/SKU, and can manage a wide range of grades/SKUs without manual reconfiguration.
Where does PM AI Agent get its source data?
PM AI Agent uses an orchestrator of large language models to combine multiple data sources: real-time machine data and RCA outputs, unstructured plant knowledge (SOPs, downtime codes, manuals), and general public manufacturing knowledge.
Can ProcessMiner actually control our equipment autonomously?
Yes. Deployments typically start with advisory dashboards and centerlining, then can graduate to closed-loop autonomous control when desired. You retain complete control over which levers are automated (such as chemistry dosing and basis weight) versus which stay manual.
Put us to the test
Prove our platform on your data.
Validate quality prediction accuracy, root-cause precision, and time-to-value on your own data. We'll work together to sync our models to your process, and you can watch your data come to life in PM Studio.
No coding required. Live dashboard in hours, results in less than two weeks.
Get in touch
Have a question?
Whether it's our platform, your process, or a free in-depth process data analysis and pilot you'd like to see in action, let us know.