SnellIoT monitors every machine in your plant — 24 hours a day. Our predictive AI engine detects failures weeks before they happen, keeping your production running without interruption.
Trusted by industrial plants across Punjab and Haryana
Reactive maintenance is the largest hidden cost in manufacturing. You fix machines after they fail — paying three to five times more than if you had caught the problem early.
A typical unplanned production halt in a mid-sized plant costs between four and twelve lakh rupees — in lost output, emergency labour, and expedited parts.
Research consistently shows reactive maintenance costs three to five times more than planned maintenance — yet most Indian factories still operate reactively.
Without monitoring, machine failure arrives without warning. There is no alert, no countdown, no data — just a stopped production line and a team scrambling to respond.
Every feature is built specifically for industrial environments — not adapted from consumer IoT. Works on any device, any platform, with no compatibility concerns.
FFT-based triaxial vibration monitoring detects bearing defects, shaft imbalance, misalignment, and gear mesh faults — weeks before visible failure.
Explore featureContinuous temperature tracking of motor windings, bearings, drives, and panels with automatic alerts when thermal limits are approached.
Explore featureEvery machine gets a live 0–100 health score updated every ten seconds — synthesizing all sensor channels into a single, instantly readable indicator.
Explore featureMachine learning models trained on industrial failure data predict exactly when a machine will fail — giving your team a specific window to act.
Explore featureWorks on web browsers, mobile phones, tablets, and desktops — any platform, any device. No app installation required. Fully responsive and always accessible.
Explore featureTiered alerts delivered via SMS and WhatsApp to the right person — operator, maintenance engineer, or plant manager — with zero false-alarm fatigue.
Explore featureOur engineers visit your plant, assess your critical machines, and design a custom monitoring configuration for your specific environment.
Sensors installed with zero production downtime. Edge gateways configured. All data encrypted and streaming securely to the cloud.
Your team gets access to the live dashboard — on any device, any platform. On-site training typically takes two to three hours.
The AI engine learns your specific machines, establishes baselines, and fine-tunes anomaly detection thresholds with your team's feedback.
SnellIoT is configured differently for each industry — because a textile ring frame has entirely different failure modes than a CNC machining centre or a food processing chiller.
Ring frames, air jet looms, compressors, and winding machines. Prevent spindle bearing failures during peak production seasons.
Explore SolutionCNC machining centres, power presses, and transfer lines. Zero tolerance for delivery delays and OEM penalty clauses.
Explore SolutionRefrigeration compressors, mixers, and packaging lines — 24/7 monitoring including overnight when maintenance teams are absent.
Explore SolutionGMP-compliant equipment monitoring with automated audit-ready logs. Protect validated production batches from equipment failure.
Explore SolutionGenerators, turbines, and large rotating assets. Critical asset protection with SCADA integration and Modbus/OPC-UA support.
Explore SolutionHydraulic presses, injection moulding, compressors, and conveyor systems. Custom configuration for any production environment.
Explore SolutionLudhiana Textile Plant
The plant was experiencing two to three unplanned motor failures per month on ring frame lines, each causing four to eight hours of production loss. No predictive capability existed before SnellIoT.
Haryana Auto Parts Manufacturer
A Tier-2 auto supplier was at risk of significant OEM delivery penalties. SnellIoT detected a progressive CNC spindle bearing defect nine days before predicted failure, enabling a planned weekend repair.
"We had three motor failures in one quarter before SnellIoT. In the first year with them, zero unplanned breakdowns. The dashboard is exactly what our team needed — clear, fast, and actionable."
"The SnellIoT team understands manufacturing. They do not just install sensors and leave. They helped our maintenance engineers understand what the data means and how to act on it immediately."
"We tried two other vendors and got dashboards with no real insight. SnellIoT predicted a compressor bearing failure eleven days before it would have happened. That single event justified the entire investment."
A practical guide to FFT-based vibration frequency analysis — what the spectral signatures of early-stage bearing degradation look like, and why most teams miss them entirely.
Overall Equipment Effectiveness is the gold standard for plant performance, but most plants only track availability. Here is why the gap matters and how to measure all three components.
Motor failures account for 38% of all industrial downtime. These are the measurable signatures — in vibration, current, temperature — that appear weeks before collapse.
The question is whether you are listening. Book a free plant assessment and we will show you exactly which machines are at risk — before they fail.
No upfront cost. No long-term commitment. Just real insights about your plant.