Reliability intelligence for process industries

Find the real root causes of failures. Not just the symptoms.

Subatix connects plant data across systems, logs, and engineering knowledge to identify why failures happen and what to fix next.

Built for mills, mines, and refineries running on legacy systems, Excel, and tribal knowledge.

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↓50%

unplanned downtime improvement, by attacking the recurring failures driving most of it

↓80%

RCA cycle time reduction - from weeks of manual stitching to hours of evidence-linked review

2 weeks

till first actionable findings on your raw data exports - no integration, no IT project

01The problem

The data exists. The visibility doesn’t. Equipment downtime compounds.

  • HistorianProcess behavior - pressures, flows, temperatures, vibration
  • CMMSFailure history, work orders, maintenance records
  • MESProduction data, downtime classifications, batch records
DATA ZONEDISCONNECTEDFAILURE?WHYANSWER SITS BETWEEN SYSTEMS
  • ReportsRCA documents, inspection findings, daily logs
  • EmailDecisions, escalations, context the system never captures
  • PeopleOperators, engineers, the why behind the data
Disconnected

When systems don’t connect, RCA takes weeks, root causes stay unclear, downtime compounds and failures repeat.

02The solution

A system that finds what others can’t see.

HISTORIANCMMSMESREPORTS & LOGSEMAIL THREADSENGINEER NOTESRANK 01Bad actor findingCRITICALRANK 02Bad actor findingHIGHRANK 03Bad actor findingHIGHRANK 04Bad actor findingMEDRANK 05Bad actor findingMEDSubatix Intelligence01Connects systems02Contextualizes data03Runs analysis04Finds root causes05Reasons and suggests fixesSEE OUTPUTS →FRAGMENTED INPUTRANKED OUTPUT
Connected

Subatix connects operational systems, engineering data, unstructured inputs, and human knowledge - then turns it into clear, prioritised failure root causes with specific corrective actions.

03The output

Not dashboards. Clear priorities.

Subatix tells teams exactly what happened, why, and what to do next. Every finding is traceable and backed by evidence - maintenance records, control system trends, lab data, shift logs, engineering reports.

Subatix Intelligence · ReliabilityEngine
Updated overnight · Ranked by severity
Copper concentrator · 5 active findings on this siteIndicative · sample output
Rank01

Copper concentrator · Flotation Row 4

System · Cell froth depth control / reagent dosing
Reagent dosing variability - recovery loss
Critical
Recovery
−2.1%
Lost Cu
$4.7M
Conf.
88%
Days
42
Evidence
Lab

LIMS - concentrate grade trending below spec for 6 weeks; assay variability tracked but not flagged to ops

Ops

DCS - collector dosing rate manually overridden across 3 shifts; never raised to MOC

Shift

Operator notes mention “froth looking off” repeatedly - never opened as work order

Action →

lock dosing setpoints under MOC · standardise froth assessment SOP · automated grade alarms with escalation rules

Rank02

Copper concentrator · SAG mill SAG-01

System · Discharge grate & liner
Ore hardness mismatch - uncoordinated feed
In RCA
Failures
5×
Downtime
384h
Loss
$3.4M
Conf.
92%
Evidence
Maint

CMMS - grate replacements cluster around hard-ore campaigns; PM strategy never updated for feed variability

Ops

Historian - mill power excursions exceed envelope on the same days; throughput pushed past safe operating window

Eng

Geology shift reports flag hard zones in advance - never linked to mill control or PM scheduling

Action →

coordinate ore feed with geology · widen grate aperture · add power-excursion trigger for pre-emptive inspection

Rank03

Copper concentrator · Ball mill BM-03

System · Trunnion bearing
Lubrication starvation - cold-start sequences
Open
Vibration
1.8× RMS
Downtime
168h
Loss
$890K
Conf.
78%
Evidence
Proc

Vibration trend - recurring spikes correlated with cold-start sequences after weekend shutdowns

Maint

CMMS - three bearing inspections in 14 months; lube oil sample records inconsistent

Shift

Start-up procedure executed inconsistently across shifts - pre-lube cycle skipped under time pressure

Action →

mandatory pre-lube interlock · lube sample protocol enforcement · revise start-up SOP

Rank04

Copper concentrator · Cyclone bank C-201

System · Apex liner / spigot
Slurry density excursions × silica content
Open
Wear rate
2.3×
Defer
24h/mo
Loss
$520K
Conf.
84%
Evidence
Ops

Density logger - running 8% above target during specific ore campaigns to maintain throughput

Lab

Metallurgy - silica content variation tracked, never linked to wear pattern across cyclones

Maint

CMMS - replacement clustering by ore type; spares unprepared for next high-silica campaign

Action →

density control retune · ore type feeds spares planning · campaign-based wear prediction model

Rank05

Copper concentrator · Conveyor CV-450

System · Belt tracking & chute geometry
Chute geometry × moisture variability - resolved
Closed
Spillage
0/mo
Down since
Aug
Saved
$310K/yr
Conf.
94%
Evidence
Shift

Daily reports flagged spillage during wet-ore periods; resolved after chute redesign in Q1

Maint

CMMS - belt tracking adjustments dropped from 12/mo to 1/mo post-fix

Eng

Engineering review confirmed root cause; chute liner replaced with curved profile

Action →

solution validated · monitoring sustained · case learnings filed for sister conveyors

04Why Subatix works

Designed for real industrial environments.

  1. 01

    Messy data ready

    Works on brownfield reality - inconsistent failure coding, fragmented exports, decades of operational drift. The data your existing tools bounce off.

  2. 02

    Cross-functional intelligence

    Connects historian, CMMS, Excel, logs, documents, and human inputs - the structured and unstructured layers in one analysis.

  3. 03

    A continuous system

    Not a one-off diagnostic. Updates as new data arrives. Your team operates it; we don't come back every quarter to rebuild the analysis.

  4. 04

    Learns over time

    Every failure analysed makes the system sharper on your assets, your patterns, your failure modes. The longer it runs, the more valuable it becomes.

05Deployment

Value in weeks, not months.

  • Works on raw exports - CMMS, historian, downtime records. Whatever you already produce.

  • No heavy integration - we land before any IT project starts.

  • First insights in 1–2 weeks - ranked findings on your data, not a generic demo.

  • Then it becomes a continuous layer - updates as new data arrives, your team operates it.

TYPICAL ENTERPRISE INTEGRATION· slow, expensive, uncertainDATA LAKEWAREHOUSEINTEGRATION?MAYBE INSIGHTSDAY 0MONTH 3MONTH 612+ MONTHSSUBATIX· ranked findings from week 1CONTINUOUS VALUE LAYERRAW → RANKEDVALUE FROM WEEK 1–2From raw exports to ranked causes - in two weeks.
Lean to land

We don’t need a data lake, a warehouse, or 12 months of integration work. Raw exports from your existing systems are enough to start. First actionable insights in 2 weeks. Integrated system in a few months.

06Expansion

Starts with reliability. Expands across operations.

Subatix initially focuses on helping reliability teams find root causes of unplanned downtime and production loss. Once deployed, the same system extends across all operations - because all of these problems originate from the same fragmented data foundation.

TODAY · ENTRY

Reliability & root cause

Recurring failures, RCA compression, action prioritisation - the pain that's most visible and most quantifiable. The wedge.

NEXT · ADJACENT

Production losses & maintenance optimisation

Same data, same plant, same trust chain. Throughput loss, backlog risk, PM effectiveness - the next layer of pain, opened by the same engine.

LATER · FULL STACK

Quality, energy, cost

The full operational stack - not from a roadmap, but because every domain originates from the same data fragmentation problem we already solved.

07Our team

Built from real operations, by people who’ve seen ops problems firsthand.

Our team has hands-on experience across heavy industries with deep understanding of the systems in use and how operations, reliability, and maintenance teams work. We’ve seen how failures happen and what it takes to figure them out - though the answers were sitting in the data available across systems. We know how to connect the dots across these systems in a safe and secured manner, so teams can use available data in full, not just see the full picture, but action it, faster.

CopperGoldAluminumRefiningPetrochemicals
Alexander Berks
Alexander Berks
CEO, ex-McKinsey

Operational excellence across process industries.

alex@subatix.comLinkedIn ↗ Alexander Berks
Vlad Rozhkov
Vlad Rozhkov
CTO, ex-SciveFlow

AI products and applied systems, full-stack development.

vlad@subatix.comLinkedIn ↗ Vlad Rozhkov
08FAQ

Questions we hear most often.

01How is this different from existing tools?

Existing tools analyze individual systems (CMMS, historian, BI dashboards).

Subatix connects data across systems, logs, and engineering inputs to identify true root causes - not just symptoms.

02Do we need to integrate all our systems first?

No. Subatix can start with raw data exports (CSV, reports, logs) and deliver initial results within 2 weeks.

Integration comes later as the system becomes continuous.

03What data does Subatix work with?

Subatix works with a combination of:

  • historian data (process signals)
  • CMMS data (failures, maintenance)
  • production data (MES)
  • logs, reports, and engineering notes

We adapt to whatever data is available.

04How do you integrate with our systems?

Subatix initially works with exported data from your existing systems.

As the system becomes continuous, we integrate directly into your environment.

05Is our data safe?

Yes. Subatix does not require uploading raw plant data to external systems.

We can operate using local exports initially and deploy on-premise for continuous use.

06What does the output look like?

A prioritized list of failure root causes with specific corrective actions.

Subatix shows which issues drive the most downtime and what to fix next.

After deployment, it also supports tracking and verifying implemented actions.

07How long does it take to see value?

Initial insights are delivered within 2 weeks.

Value increases over time as the system becomes continuous and more data is incorporated.

08Is this replacing our reliability team?

No. Subatix augments reliability teams by handling data analysis and identifying root causes.

Engineers remain responsible for decisions, execution, and field operations.

09How accurate are the results?

Subatix combines data from multiple sources and cross-validates patterns to identify consistent root causes.

Accuracy improves over time as more data is processed.

10Will this work with messy CMMS and brownfield data?

Yes. Subatix is designed for brownfield environments with inconsistent asset naming, incomplete failure coding, and fragmented data.

It does not require a clean data warehouse to deliver value.

11How do you handle unstructured data like logs and reports?

Subatix uses AI models to extract and connect information from logs, reports, and other text sources, combining it with structured data to provide full operational context.

12What industries do you focus on?

Process industries such as metals, mining, chemicals, refining, and power generation - where operations are complex and data is fragmented.

13Why hasn't this been solved before?

Because operational data is fragmented across systems and unstructured sources, and traditional tools cannot combine them effectively and surface actionable insights.

Recent advances in AI now make this possible.

Which failure on your reliability list has been there for two years? And what would it be worth to actually close it?

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What happens next

A 30-minute call. Two questions. No deck.

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