Dylan Hoback
Accu-Tube
My Praxie analytics software transformed our operations, enabling data-driven decisions and streamlining our manufacturing process.
The chart went out of control at 2am. Somebody initialled it at 8.
Replace paper control charts and after-the-fact reviews with AI that watches every characteristic in real time — detecting drift, flagging the rule that broke, and telling someone who can act.
$0
Send us one month of your real process data
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Free pilot on your own process data. You keep what we find.
AI statistical process controlfor process and quality engineers
Customer Success Stories
Dylan Hoback
Accu-Tube
Jason Carpenter
Environmental Pest Management
With Praxie, I found a way to take what was in documents and spreadsheets and provide my team with a visual application environment to drive our strategy with full accountability.
Elizabeth Pridham
Perfection Fresh
Praxie dramatically improved our process through digital transformation. We now have visibility and can drive decisions at a fraction of the time.
Scott Russell
NUCOR Vulcraft
I would heartily recommend the Praxie team to any organization seeking to seriously undertake a lasting and successful innovation process.
Mike Bainbridge
Dover Food Retail
Our MFG Ops application greatly improved our daily management initiatives. It is easy to see how we are doing, identify issues, and track improvements—no matter where we sit.
Jeff Piotrowicz
ChemLink
With Praxie we've created a way to report on complex projects that gives management full visibility. Executives have visibility to projects, assignments, and more at their fingertips.
Maureen Thompson
American Nurses Association
Our Praxie App makes it easy to track progress on strategic objectives across the organization and includes an executive-level dashboard with real-time reports to the board on key initiatives.
Tom Anderson
Springfield Armory
Praxie is used every day to track and analyze every aspect of production, quality, safety, and more. We improved quality by 10%.
Peggie Pelosi
Innovators Alliance
Almost overnight, Praxie created a customized solution for our 100 member organizations across Canada to drive strategy and innovation.
Kate Merton
Anthem
Praxie's innovation solution stood out from other options because it can be customized so quickly to fit our exact process requirements. Plus, it is incredibly easy to use and manage.
The signal was there. Nobody was watching.
Plotting the chart was the easy part. Acting on it, while the process is still running, is the job.
“How did a whole batch ship out of tolerance?”
“I plot the points. Nobody told me what to do when it moves.”
A folder of charts, signed off daily, reviewed never.
You do not need more charts. You need the process to raise its own hand — before the batch is scrap.
If you own process capability
Is this your process?
Most process and quality engineers recognise at least four of these. If you recognise six, the rest of this page is written for you.
- Charts are filled in by hand and reviewed the next day.
- Out-of-control signals are initialled rather than acted on.
- Nobody is sure which rule set is actually being applied.
- Capability studies are done for the customer, not for the process.
- Drift is found when the batch is inspected, not while it runs.
- Operators plot points without being told what to do about them.
- Scrap is discovered downstream, hours later.
- “When did that start drifting?” takes a week to answer.
None of this is a charting problem. It is a response problem.
Is this you?
Worked example — multi-characteristic production processControl charts used to be reviewed after the shift.
Next day↓Livewhen drift is actually detected
Dozens of characteristics, paper charts at the machine, and a review that happened the following morning.
Because signals were seen hours after they occurred, a process could drift for an entire shift before anyone acted — and the first real evidence was often scrap found downstream.
With AI monitoring every characteristic as data arrives, the rule that broke is identified and routed to someone who can act, so the response happens while the process is still running.
Monday, 6am
What you walk onto the floor with
Today
A folder of signed charts.
- Plotted by hand, reviewed next day
- Signals initialled, not acted on
- Drift found at final inspection
- Scrap discovered downstream
→
With Praxie
A process that flags itself.
- Every characteristic monitored as data arrives
- The rule that broke identified automatically
- Routed to someone who can act
- Response while the process still runs
Key ROI Elements
30%
Less Process Variation
Detect shifts earlier and reduce scrap and rework.
40%
Faster Signal Response Time
Cut delays from signal to action to verification.
25%
Higher Process Capability
Improve Cpk and keep processes in control.
15%
Lower Cost of Quality
Reduce scrap, rework, and repeat defects.
Fewer
Defect Escapes
Catch issues before they reach the customer.
Higher
Process Yield
Improve first-pass yield across every line.
See Praxie in Action Now
Which process drifts without anyone noticing in time?
Now select a day and time below.
Why Charts Reviewed Later Catch Nothing
Spreadsheets &
Manual Logs
- Reactive tracking
- Paper-based control charts
- Limited process history
- Hard to prioritize signals
- Higher defect risk
ERP / QMS
Quality Modules
- Connected to enterprise data
- Often rigid workflows
- Slow field adoption
- Heavy configuration
- Limited AI guidance
Traditional
SPC Tools
- Good control charting
- Capability study support
- Can become data-entry heavy
- Limited operational context
- Often weak analytics
Point
Predictive AI Tools
- Useful for narrow use cases
- Detects some patterns
- May require data projects
- Disconnected from execution
- Limited SPC workflows
★ BEST FIT
Praxie AI-Powered
Statistical Process Control
- AI control charts, capability & MSA
- Predictive alerts and risk prioritization
- Connects ERP, QMS, MES, gauges & sensors
- Dashboards, workflows & operator guidance
- Faster deployment, lower complexity
SPC workflow flexibility
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✓
Real-time signal response
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✓
AI shift detection & recommendations
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✓
✓
Charts, capability & MSA
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✓
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✓
Connected measurement, gauge & operations data
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✓
Speed to deploy and adapt
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✓
Why Praxie
Stands Out
Stands Out
More flexible than rigid QMS and ERP modules
Far more automated than spreadsheets and manual logs
Broader than point SPC charting tools
Faster to deploy than heavy QMS replacement projects
Questions Process Engineers Ask Us First
The objections we hear in the first 20 minutes — answered plainly.
1
How does AI improve statistical process control — and can my team trust it?
Answer: The AI helps quality teams make better decisions by analyzing control charts, measurement data, capability studies, inspections, and operator notes. Recommendations are explainable, so teams can see why a process needs attention and stay in control of every decision.
2
Can this reduce scrap, rework, and defect escapes?
Answer: Yes. AI-powered SPC identifies early warning signs, recurring signals, drifting processes, and high-risk characteristics before they produce defects. This helps teams shift from after-the-fact inspection to real-time, predictive process control.
3
How does the system help manage signals and corrective-action priorities?
Answer: The AI can help create, categorize, prioritize, and route corrective actions based on characteristic criticality, defect risk, production impact, required skills, data availability, and process history. Teams get a clearer view of what needs to be done first and why.
4
Will this help us find root causes and recurring process issues?
Answer: Yes. The system analyzes patterns across out-of-control signals, measurement data, corrective actions, inspections, and operator comments to identify repeat problems, likely root causes, and improvement opportunities across characteristics, lines, plants, or suppliers.
5
Is this better than spreadsheets, a basic SPC tool, or manual control charts?
Answer: Yes. Traditional tools often store SPC data but do not actively interpret it. AI-powered statistical process control connects measurement data, control charts, KPIs, and process context so teams can predict issues, optimize control plans, and continuously improve capability.
Bottom line: AI-powered statistical process control helps teams reduce variation, prioritize the right signals, improve process capability, and move from after-the-fact inspection to proactive, real-time process control.
Which process would you watch first, if it flagged itself?
Send us one month of your real process data. We’ll show you what Praxie would have caught — your characteristics, your rules, your drift.
1Send us a month of data230-minute review3Free pilot on your data
See Praxie in Action
No cost, no obligation — and you keep what we find either way.