exOS · AI-native software for operations
Run your operations on software that reasons.
Exlens gives you two things: a reasoning layer that sits on top of the systems you already run — EAM, SCADA, historians, ERP — and a set of AI-native modules you can deploy on their own. Predict failures, trace root cause, optimize every schedule. Keep your stack.
Built for:
Manufacturing
·
Utilities & grid
·
Water & wastewater
·
Energy & pipelines
·
Facilities & infrastructure
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Heavy industry & process
How it fits together
One reasoning layer.
Modules that stand on their own.
Exlens never inserts itself between you and your data. SureLock reasons across whatever you have — your systems of record, our modules, or both. The modules are standalone AI-native products that run alongside your stack, not in the middle of it.
SureLock — the AI reasoning layer
Sits on top of everything below. Predicts, traces, and optimizes across every source.
exOS modules
AI built in
Maintenance · CMMS/EAM
Inventory
Manufacturing Execution
Quality · QMS
Your existing systems
unchanged
EAM / CMMS (Maximo, SAP PM)
SCADA
Historian (PI)
MES · ERP · GIS
Modules run in parallel with the systems you own. SureLock sits on top of both.
Two ways to buy
Start with the layer.
Or start with a module.
Both are AI-native. The only question is where you want intelligence first — across the systems you already run, or in a capability you’re ready to modernize.
Path 01 · The AI layer
SureLock, over your existing systems.
Keep Maximo, SAP, your SCADA and historian. SureLock connects across them and turns them into one system you can question — failure predictions, traced root cause, optimized schedules. Nothing gets replaced or migrated.
Best when: your systems work, but the answers are buried inside them.
Path 02 · AI-native modules
exOS modules, with AI already inside.
Modernizing maintenance, inventory, execution, or quality? Deploy an exOS module on its own. The intelligence isn’t an add-on; it ships in the product. Each module runs standalone and connects to the rest when you’re ready.
Best when: you need new capability fast, without a multi-year rollout.
Take both, and one reasoning layer spans your exOS modules and your legacy systems alike.
What “AI-native” actually means
Most software stores your data. Exlens reasons about it.
Both are AI-native. The only question is where you want intelligence first — across the systems you already run, or in a capability you’re ready to modernize.
Systems of record answer:
How many work orders closed last month?
A count. Whether the right work got done is anyone’s guess.
exlens answers
Which assets fail next quarter — and what does waiting cost?
A ranked list, the predicted failure window, and the cost of doing nothing.
the reasoning layer
Three things it does across every system you run.
SureLock is the engine inside every exOS module — and it runs just as well on top of the EAM, SCADA, historian, and ERP you already have. It learns how your assets behave, follows cause through the chain, and shows its work.
Failure & defect prevention
Predict which assets are trending toward failure — transformers, breakers, pumps, pipeline segments, production equipment — and act before they cause an outage. SureLock learns each asset’s normal behavior and flags the drift early.
Root cause analysis
When something fails, trace it to its true source across SCADA logs, sensor history, asset records, and work orders — not the symptom that tripped the alarm. Recurring faults get linked back to one underlying cause.
Scheduling optimization
Plan maintenance windows, outages, and crew dispatch against real constraints — asset risk, load, weather, crew availability, spares on hand. SureLock optimizes the plan and updates it as conditions change.
1.understand
2.Gather
3.Reason
4.Answer
Utilities
You ask
Why does Feeder 7 keep tripping?
It answers
Substation 3 / Feeder 7
Momentary outages rose 2.8× over six weeks. Root cause: insulation aging on a legacy cable section, pushed past thermal limits by the load shift after the Feeder 4 reconfiguration — tripping under peak afternoon load.
Traced through
SCADA trip logs → post-switching load profile → asset register & cable age → 22 momentary events, 18 sharing one thermal-stress signature.
Prioritize the cable section in the summer window; rebalance load to Feeder 9 meanwhile. Est. resolution: 70–80% of momentary outages on Feeder 7.
Manufacturing
You ask
What's going wrong at Station 12?
It answers
Station 12 / Rear Door Assembly
Gap-tolerance failures rose 3.2× over 72 hours. Root cause: fixture calibration drift at Station 9 shifted B-pillar alignment by 0.4 mm, pushing door-seal compression out of spec on 34% of units.
Traced through
Station 9 fixture logs → B-pillar dimensional data → Station 12 gap readings → 47 logged defects, 43 sharing one root signature.
Recalibrate Station 9 fixture. Est. resolution: 80–90% of current defect volume.
The modules
Or deploy an AI-native module on its own.
Each module is a complete product — built around the same reasoning engine, not reporting bolted on top of one. Some span every industry; some are built for production sites. All are AI-native.
Asset health / prediction view
Maintenance · CMMS / EAM
Assets, work orders, PM programs, and full history in one AI-native system. It predicts which assets fail next from sensor and historian data, quantifies the cost of an outage, and schedules around real risk — not a fixed calendar.
Ask it:
Which assets fail next, and what does the outage cost?
Inventory / spares view
Inventory management
Stock, lots, and consumption tied to the work that uses them — production materials and MRO spares alike. It sees shortages before they delay a job and flags critical parts quietly draining capital. Reordering follows real demand, not fixed min/max.
Ask it:
Which assets fail next, and what does the outage cost?
Live line / station view
Manufacturing execution
Live work orders, routing, and unit-level traceability for production sites. It spots the constraint forming before it stalls the line — and names the station and the reason, not just the slowdown.
Ask it:
Why is Line 3 slower than the same shift last week?
Defect cluster / root-cause view
Quality · QMS
Inspection, defects, NCRs, CAPA, and FMEA tied to the unit. It finds the one root cause behind a cluster that looks unrelated, surfaces every unit sharing it, and drafts the CAPA with evidence attached.
Ask it: