Engineers building the visibility layer for critical assets.
Novek is a UAE engineering company. We give asset owners and operations teams earlier visibility into the equipment that creates the most operational risk — so failures are caught as drift, not as complaints, downtime, or emergency cost.
A Dubai engineering team. Independent by mandate. Focused on critical assets.
Novek is a small, focused engineering team headquartered in Dubai, United Arab Emirates. We are mechanical and electrical engineers with backgrounds in industrial condition monitoring — vibration, thermal, and electrical health on critical rotating and pressurised equipment, from offshore platforms to industrial plants.
What we build is straightforward: a continuous IoT visibility layer over the mechanical and electrical assets that carry the most operational risk in UAE commercial and industrial portfolios — chillers, pumps, AHUs, compressors, tanks, and critical service equipment. The platform is independent of the FM provider, sits alongside (not inside) the BMS, and is built so the asset owner owns the data from day one.
We are not a CMMS, not an FM provider, and not a BMS replacement. We are the independent measurement layer that none of those systems exist to be.
- HeadquarteredDubai, United Arab Emirates
- DisciplineMechanical & electrical engineering
- StackIoT + LoRaWAN + analytics
- Data residencyUAE-resident hosting
Most failures are not sudden. They are missed.
Across malls, towers, industrial sites, district cooling plants, and utility infrastructure, the equipment that carries the most risk usually fails after weeks or months of quiet drift. A pump behaves differently. A tank level becomes abnormal. A compressor runs outside its normal pattern. A small leak begins where nobody checks often enough.
The signal is there. But manual rounds, fragmented reports, busy site teams, and long spare-part lead times mean the issue is often discovered only after it becomes visible, urgent, or complained about. That is the gap we exist to close — surfacing the signal earlier, in language operations teams and asset owners can act on.
The first warning should not come from a tenant, a complaint, or an emergency callout. If the asset has been drifting for weeks, someone should have known.
Four principles we don't compromise on.
- Principle 01
Independent by design
Novek sits outside the FM provider's reporting chain. The asset owner gets a second opinion that doesn't depend on the same party being measured.
- Principle 02
Operational language, not sensor language
Findings are framed as risk, downtime, and AED exposure — not vibration spectra. The people who can act on the issue should understand it in seconds.
- Principle 03
No silent degradation
The gap between manual checks is where asset value disappears. Novek measures continuously and surfaces drift before it becomes an event.
- Principle 04
Your data, your building, no lock-in
Open standards. Full export. UAE data residency. The asset owner owns all data from day one — no proprietary protocols, no contractual traps.
Start small. Prove value. Expand on what the data proves.
Engagements typically begin as a focused Failure Visibility Assessment on one site, one asset group, and one measurable operational risk. From there, coverage expands by site, sector, or asset category — driven by what the data shows, not by a sales target.
- 01
Failure Visibility Assessment
Selected critical assets are instrumented and monitored. A clear baseline is established. Risks are mapped.
- 02
Continuous detection
Abnormal behaviour, drift, and signal cascades surface in operations-team language — well before the issue becomes visible to tenants or management.
- 03
Expand by site or asset group
Coverage extends one decision at a time. Each expansion is justified by the data from the previous one — not by promise.
One site. One asset group. One measurable risk.
Novek does not need to begin as a full-platform rollout. Start with the assets most likely to create complaints, downtime, or emergency cost — then expand based on what the data proves.