From Operational Data to Operational Intelligence
APPEX360 connects operational data, assessments, KPIs and enterprise systems to create a trusted foundation for evidence-based decisions.
Where the data comes from
SourcesEach source is validated before it can influence any KPI or reasoning output.
What APPEX360 builds
LiveSix stages, one governed path. Nothing reaches the executive layer without passing validation.
Keep your systems. Add the intelligence layer.
APPEX360 is designed to sit above the systems you already run. Sources are ingested, validated and mapped into one unified operational model — and the status of every named system is stated openly.
CMMS / EAM
ERP / Finance
Operations / IoT
Files & spreadsheets
Manual records
Connectivity options
Stated plainly: named third-party products are shown as integration options and roadmap items. APPEX360 does not claim a live production connector for a product unless it is marked Available. File imports (Excel, CSV, templates) and manual entry are available today.
The strongest and safest place to start is your existing CMMS and ERP export — validated before it reaches any KPI.
Know what your data can support — and what it cannot
Before any KPI or recommendation is issued, APPEX360 scores the health of the evidence. Weak data produces restricted intelligence, not confident-sounding answers.
Overall Data Quality Score
DemonstrationEnough evidence for some conclusions — not enough for others. APPEX360 reports the difference instead of hiding it.
Shown with demonstration values. Scores are produced from your own source data at import time.
Critical data issues detected
5 foundMissing PM history
No PM records found for Jun–Aug 2026 for 14 of 52 assets.
Duplicate work orders
318 work orders share an identifier across two systems.
Inconsistent asset identifiers
P-101 / P101 / PUMP-101 refer to the same asset.
Orphan downtime records
96 downtime events are not linked to any asset.
Stale data
Two sources have not refreshed in 41 days.
Missing PM history detected.
“No PM records found for Jun–Aug 2026 for affected assets.”
Impact on analysis
APPEX360 does not let APPEXi reason confidently over unreliable evidence. Gaps are disclosed, and affected conclusions are withheld until the evidence improves.
Scores and issue lists are generated from your imported data. The figures above are demonstration values.
One operational context for every asset
Instead of looking through multiple systems, APPEX360 consolidates everything known about an asset into a single profile — the same context is then used for every KPI, analysis and reasoning step.
CMMS work orders
187 open / closed jobs linked to P-101
PM history
14 PM jobs found; Jun–Aug gap flagged
Failure history
Seal and bearing failures dominate
Downtime
Unplanned downtime this year to date
ERP information
Parts, labour and contractor cost visible
Criticality
Drives the KPI weighting and alerts
Operational KPIs
Recomputed whenever source data changes
Maintenance status
Two PM tasks past due date
“Insted of chasing the same asset across six screens, APPEX360 creates one operational context — and every conclusion can be traced back to it.”
P-101 is a demonstration asset. In your environment the same profile is built from your own CMMS and ERP records.
Structured maturity, not opinion
Eleven discipline frameworks, each broken into pillars, subcategories and questions, produce a measured view of operational maturity — the assessment evidence sits alongside your operational data.
Drilling into TPM
LivePillar 1 — Autonomous Maintenance
Demonstration maturity scores. Real scores are produced from your responses.
Example questions
Sample1.1 Basic Conditions
Are cleaning, lubrication and tightening standards defined, displayed and maintained at the equipment?
1.3 Abnormality Detection
Can operators identify and tag abnormalities using a defined, agreed standard?
1.5 Root Cause Elimination
Are recurring abnormalities eliminated at source rather than repeatedly repaired?
Assessment scoring logic is unchanged by this tour. The tour only presents it.
Every number carries its source
Hover any KPI to see where the value came from, which period it covers and how much the data can be trusted — the same discipline APPEXi applies when it reasons.
Availability vs PM compliance — last 9 months
DEMO DATAIllustrative series produced from demonstration values. Trend rendering is live; the values are not customer results.
Where the reliability risk actually sits
Maintenance work is split into preventive, planned, unplanned and breakdown activity, then ranked by asset — so the conversation moves from “we are busy” to which assets are driving the loss.
Maintenance mix — 6 months
DEMO DATATop assets by breakdown frequency
DEMO DATA| Asset | Breakdowns | MTBF | Trend |
|---|---|---|---|
| Pump P-101 | 11 | 120 hrs | |
| Compressor C-201 | 8 | 214 hrs | |
| Conveyor CV-03 | 6 | 268 hrs | |
| Motor M-110 | 5 | 332 hrs | |
| Gearbox GB-07 | 5 | 348 hrs |
P-101 alone accounts for 31% of breakdown events across the five ranked assets.
Declining — failures getting closer together
Rising — repairs taking longer
Below the 90% claim — see conflict detection
All figures on this page are realistic demonstration values, clearly marked. No customer results are shown or implied.
A common comparison framework across sites
The same definitions, the same calculation rules, the same data-quality test — so sites can be compared fairly. Where a site’s evidence is too weak, APPEX360 says so instead of producing a misleading ranking.
| Site | Availability | MTBF | MTTR | PM compliance | Breakdowns / mo | Data quality |
|---|---|---|---|---|---|---|
| Site A | 91.2% | 186 hrs | 6.4 hrs | 58% | 35 | Partial |
| Site B | 94.6% | 410 hrs | 3.9 hrs | 86% | 12 | Good |
| Site C | 88.4% | 242 hrs | 5.8 hrs | 71% | 21 | Partial |
| Site D | 92.8% | 318 hrs | 4.4 hrs | 79% | 15 | Good |
| Site E | Not comparable | — | — | 34% | — | Insufficient evidence |
PM compliance by site
DEMO DATASite E is not ranked
Insufficient evidenceSite E returned 34% data quality with a five-month downtime gap. APPEX360 reports it as not comparable rather than placing it in a league table on unreliable evidence. This is the same fail-closed rule APPEXi applies in conversation.
No customer sites, results or benchmarks are shown or implied.
What people believe, versus what the evidence shows
Three sources describe the same subject. Because APPEX360 holds them side by side, the disagreement becomes visible — and it becomes the most valuable finding in the assessment.
Questionnaire
Assessment“We have a formal PM program with >90% compliance.”
Self-reported. Weighted as a claim, not as evidence.
KPI data
CalculatedCalculated from CMMS PM schedules and completed jobs, Jun–Aug 2026.
Client claim
Conversation“Our PM compliance is around 90%.”
Stated in review. Held as a claim requiring corroboration.
A 32-point gap between the claim and the calculated value is itself the finding. Before any PM effectiveness conclusion is drawn, APPEX360 first tests whether the gap is a performance problem or a data problem.
“APPEX360 does not simply accept the claim. It cross-validates the available evidence — and when the claim and the data disagree, it shows you both.”
The questionnaire text, claim and figures in this section are demonstration values used to illustrate the conflict-detection principle.
Meet APPEXi
Evidence-aware AI for operational intelligence. APPEXi is built to challenge unsupported claims and ask for evidence before it offers a diagnosis — and it fails closed rather than guessing.
The evidence ladder
LiveHigher evidence produces higher confidence and safer reasoning.
How the reasoning is governed
Hypothesis governor
Weak or unsupported claims are held as hypotheses. APPEXi will not convert them into stated facts.
Reasoning Control Layer
Governs how a conclusion may be formed, and what must be established first.
Claim interrogation
Unsupported qualitative claims trigger questions — actual value, target, baseline, period, component, denominator.
Fail-closed
Where evidence is insufficient, APPEXi withholds the conclusion instead of estimating around it.
APPEXi is presented here only with capabilities that are actually implemented. Nothing on this page describes future functionality as available.
A conversation that challenges the assumption
A short demonstration of APPEXi spanning OEE, availability, breakdowns, PM, reliability, CMMS history, skills, maintenance practice and data quality — in one governed exchange.
Our OEE is high, but our breakdown frequency is also high. What’s going on?
I would not treat high OEE alone as evidence of healthy asset performance. OEE and breakdown frequency measure different things, and they can rise together.
Before I attribute a cause, I need to establish what the numbers actually are. I have two questions.
1. What is the actual OEE value, over which period, and against which target — and how is it split across Availability, Performance and Quality?
2. What is the breakdown count over the same period, and what operating hours form the denominator?
I am holding this as a hypothesis, not a finding. No diagnosis is issued until the evidence is established.
“High” is a comparative term with no baseline attached. The Reasoning Control Layer requires a value, a target and a period before any causal claim can be formed — so it interrogates rather than diagnoses.
OEE is 84%. Breakdowns are about 35 a month. PM compliance is 58% and MTBF around 120 hours on Site A.
That changes the picture. The OEE figure is now established, so I can move from questioning to analysis — with one caveat on data quality, below.
Placing Site A beside Site B, using the same definitions:
Your OEE is high, but the breakdown pattern suggests another issue.
Three observations are worth separating:
1. Breakdowns of 35 per month with an MTBF of 120 hours is a high-frequency failure pattern. That is not consistent with healthy asset performance, whatever the OEE figure shows.
2. PM compliance of 58% means planned work is not being executed. Rising breakdown frequency alongside falling PM compliance points to a maintenance-effectiveness problem before it points to an equipment problem.
3. OEE can stay high while short-duration losses are absorbed elsewhere in the line. A high OEE with high breakdown frequency raises a question about the OEE calculation itself — particularly whether short stops are being captured.
Before attributing the result to equipment performance, I would check PM effectiveness, failure modes and asset-level breakdown concentration.
One restriction: the PM gap for Jun–Aug on Site A limits how far the second observation can be taken. Site-level conclusions are available; asset-level PM effectiveness conclusions are not.
Recommended next actions
Gated on evidenceInvestigate recurring failure modes
Start with the dominant failure mode across the top five assets by breakdown frequency.
Review PM effectiveness
58% compliance — establish whether the plan is wrong, the execution is wrong, or both.
Examine critical asset history
P-101 drives 31% of breakdown events across the ranked assets.
Review technician / fitter capability
Recurring seal and bearing failures can indicate a skills or procedure gap.
Verify the OEE calculation
Check whether short-duration losses are captured in the availability denominator.
Validate data quality first
Resolve the PM history gap before any asset-level PM conclusion is issued.
Illustrative exchange showing the default interrogation-first behaviour. It is not a transcript of a customer conversation.
You should not have to trust the AI
Every factual statement APPEXi produces carries an optional View evidence control. Open it and you see the source, the dataset, the version and the date — and the chain that connects them.
Breakdown frequency on Site A rose from 26 to 35 events per month between January and September 2026, while PM compliance fell from 84% to 58%.
Provenance
End-to-end lineageEvery statement can be walked backwards to the record it came from. If the lineage cannot be completed, the statement is not presented as established.
What this changes
APPEXi does not ask you to trust the AI. You can inspect where the statement came from, when it was pulled and what condition the source was in — and you can disagree with the reasoning while still seeing the same evidence.
Stated plainly
The example above uses demonstration data. MEX appears here as an example CMMS system name only — APPEX360 does not claim a live production MEX connector. Evidence tracing works with any validated import.
From insight to a tracked action
An insight that does not become an owned action changes nothing. Every recommendation carries its evidence, and every action carries an owner, a due date and a status.
Investigate P-101 failure history
Recurring breakdowns are concentrated around Pump P-101 — 11 events this year, 31% of events across the top five assets. Establish the dominant failure mode before any further maintenance spend is committed.
Owners, dates and statuses shown are examples of the action-planning structure, not live customer commitments.
Turn Operational Complexity Into Executive Clarity
APPEX360 connects the operational evidence. APPEXi helps interpret it within governed reasoning boundaries.
Ready to see it on your own data?
Start with what you already have. Import a CMMS or ERP extract, run the data health check, and see what your evidence can — and cannot — support.
Capability labels used throughout this tour: Live · Demonstration · Import-based · Roadmap. Nothing in this tour presents roadmap or planned capability as live functionality.
Available, In Development, Coming Soon
We publish what is released and what is not. Each assessment below is listed exactly as its product record states — released work is marked Available, and announced work is marked Coming Soon.
Available 6
- 5S Assessment Released and usable now.
- Lean Assessment Released and usable now.
- Operational Excellence Lite Released and usable now.
- Reliability Assessment Released and usable now.
- Six Sigma Assessment Released and usable now.
- TPM Assessment Released and usable now.
In development 1
- Pilot Workshop Assessment By invitation only. Not part of the general release.
Coming Soon 2
- Energy Management Assessment Announced. Currently in internal review. Not yet available to use.
- Safety Culture Assessment Announced. Currently in preview. Not yet available to use.
A note on RCM. Reliability-Centred Maintenance is the methodology behind the Reliability Assessment — it is not a separate product, and it is not listed as one. Maintenance strategy, criticality and failure-mode thinking are assessed inside that bank.