Dylan Hoback
Accu-Tube
My Praxie analytics software transformed our operations, enabling data-driven decisions and streamlining our manufacturing process.
You drew the fault tree after the failure. Twice.
Replace one-off fault trees in a drawing tool with AI that builds the logic from your own failure history — so the analysis is reusable, consistent, and available before the next failure rather than after it.
$0
Send us one failure you have analysed before
See Praxie in Action Now
Free pilot on your own failure data. You keep what we find.
AI fault tree analysisfor reliability 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.
Every analysis starts from a blank page.
Drawing the tree was the easy part. Making it reusable, so the next engineer does not start over, is the job.
“We need the root cause analysis within eight days.”
“Someone analysed this in 2023. I cannot find it.”
A diagram in a file share, built once, never opened again.
You do not need better diagrams. You need the analysis to accumulate — so each failure teaches the next one.
If you own root cause
Is this your analysis?
Most reliability and quality engineers recognise at least four of these. If you recognise six, the rest of this page is written for you.
- Every fault tree is built from scratch.
- Two engineers analyse the same failure differently.
- Past analyses exist but nobody can find them.
- Probability estimates come from judgement with no record of why.
- The tree is drawn to satisfy a customer, not to prevent recurrence.
- Contributing causes are omitted because nobody thought of them.
- There is no link between the analysis and the corrective action.
- “Have we seen this before?” cannot be answered.
None of this is an analysis problem. It is a reuse problem.
Is this you?
Worked example — multi-site reliability teamEach analysis used to start from a blank page.
Blank↓Accumulatedwhat each new analysis starts from
Years of failure history, dozens of fault trees, and no connection between any of them.
Because each tree was drawn independently in a diagramming tool, the knowledge stayed with whoever built it — so recurring failures were re-analysed from scratch, sometimes reaching different conclusions.
With AI building the logic from your own failure history, prior analyses inform the next one, contributing causes are suggested from what actually happened, and the tree stays linked to the corrective actions it produced.
Failure review, 9am
What you walk into the failure review with
Today
A blank page and a deadline.
- Every tree built from scratch
- Past analyses unfindable
- Conclusions vary by engineer
- No link to corrective action
→
With Praxie
Everything you already know.
- Logic built from your failure history
- Prior analyses surfaced automatically
- Contributing causes suggested from evidence
- Linked to the actions it produced
Key ROI Elements
30%
Fewer Repeat Failures
Identify true root causes and stop recurrence.
40%
Faster Analysis Cycle Time
Cut delays from incident to logic tree to verified action.
25%
Stronger Analysis Rigor
Keep logic, evidence, and assumptions documented.
15%
Lower Failure Cost
Reduce scrap, rework, warranty, and repeat incidents.
Fewer
Missed Causes
Connect every branch to evidence and verification.
Higher
Safety and Availability
Reduce risk exposure and protect uptime.
See Praxie in Action Now
Which failure have you analysed more than once?
Now select a day and time below.
Why Fault Trees Die in a Drawing Tool
Spreadsheets &
Manual Logs
- Reactive tracking
- Static diagrams and spreadsheets
- Limited analysis history
- Hard to prioritize causes
- Higher recurrence risk
Reliability / Safety
Analysis Suites
- Connected to enterprise data
- Often rigid workflows
- Slow field adoption
- Heavy configuration
- Limited AI guidance
Diagramming
& RCA Tools
- Good diagram control
- Standard gate and symbol support
- Can become data-entry heavy
- Limited operational context
- Often weak analytics
Point
Predictive AI Tools
- Useful for narrow use cases
- Detects failure patterns
- May require specialist training
- Disconnected from execution
- Limited corrective action workflows
★ BEST FIT
Praxie AI-Powered
Fault Tree Analysis
- AI cause logic, cut sets & actions
- Predictive alerts and risk prioritization
- Connects ERP, MES, QMS, CMMS & quality
- Dashboards, workflows & engineer guidance
- Faster deployment, lower complexity
Analysis workflow flexibility
–
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✓
Real-time incident response
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✓
AI cause suggestion & recommendations
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–
–
✓
✓
Top events, gates & basic events
–
◐
✓
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✓
Connected incident, evidence & 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 reliability suites
Far more automated than spreadsheets and manual logs
Broader than point diagramming tools
Faster to deploy than heavy reliability software rollouts
Questions Reliability Engineers Ask Us First
The objections we hear in the first 20 minutes — answered plainly.
1
How does AI improve fault tree analysis — and can engineers trust it?
Answer: The AI structures the analysis faster by suggesting likely failure paths, organizing causes into logical branches, and connecting evidence from incidents, inspections, alarms, and quality data. Engineers stay in control because every AI suggestion can be reviewed, edited, accepted, or rejected.
2
Does AI replace the reliability engineer or RCA facilitator?
Answer: No. AI acts as a guided analysis partner. It removes blank-page work, speeds up data review, and helps teams avoid missing contributing causes — but the final logic, assumptions, and corrective actions are still validated by subject matter experts.
3
Will AI help us quantify risk and prioritize which causes matter most?
Answer: Yes. The AI ranks likely contributors based on evidence strength, recurrence, severity, historical frequency, detectability, and business impact. Teams get a clearer view of which failure paths to act on first and why, so corrective action lands on the highest-risk causes.
4
Can it connect fault trees to real manufacturing data and corrective actions?
Answer: Yes. It connects to sources such as ERP, MES, QMS, CMMS, sensor logs, production records, NCRs, CAPAs, downtime codes, inspection results, and operator notes — then translates validated root causes into corrective actions, owners, due dates, and verification steps.
5
How is this different from a spreadsheet, Visio diagram, or static template?
Answer: Traditional tools capture the diagram but do not actively help build the analysis. AI-powered fault tree analysis ingests evidence, recommends cause branches, identifies gaps, summarizes logic, generates action items, and keeps the analysis connected to live operational context — which also makes audits and management reviews far easier to support.
Bottom line: AI-powered fault tree analysis helps teams build better cause logic, connect evidence faster, prioritize risk, and turn root cause findings into corrective action without giving up expert control.
Which failure would you analyse first, if the work carried forward?
Send us one failure you have analysed before. We’ll show you what Praxie would build — your history, your logic, your causes.
1Send us a failure230-minute review3Free pilot on your data
See Praxie in Action
No cost, no obligation — and you keep what we find either way.