IoT sensors and AI-powered predictive maintenance flag early signs of solar borehole pump failure — before a community loses access to water.
Sense → connect → predict → alert → repair. Every stage keeps a human in control of the final decision.
Vibration, current, voltage and solar sensors continuously monitor pump behaviour.
Telemetry transmits securely through AWS IoT Core, even over poor connectivity.
Azure Machine Learning analyses patterns and flags anomalies against normal behaviour.
Pump Pulse raises a maintenance risk — never a guarantee of failure, always a probability.
AI drafts a work order and routes it to the right qualified technician nearby.
Identify abnormal pump behaviour early, while there's still time to act.
Give technicians advance warning instead of an emergency call-out.
Extend the useful life of donor-funded and public water infrastructure.
Help communities keep reliable access to the water source nearest to them.
Pump Pulse never tells an operator a pump will fail on a specific day — it shows the evidence and an estimated window.
Vibration, current or solar output drifts outside the normal operating range.
A health score and failure-risk band are calculated from historical patterns.
Every prediction ships with a confidence percentage — never framed as certainty.
AI generates the recommended action, required skills and equipment.
A technician or manager can always override the recommendation, with a reason logged.
Increasing motor vibration over 8 days.
Possible bearing degradation — not yet confirmed.
7–14 days — inspection recommended, not an emergency.
Pump Pulse is not locked to a single cloud or a single AI vendor. A routing layer sends each task to whichever provider handles it best.
The connectivity backbone. Every sensor authenticates with a unique certificate and publishes telemetry — vibration, current, voltage, solar output, flow, water level — into a secure, time-stamped pipeline built to tolerate patchy rural connectivity.
Runs the anomaly-detection and failure-prediction models — turning raw telemetry trends into a health score, a failure-risk band, and the specific signals behind each prediction.
Drafts work orders, technician-facing explanations and operational summaries in plain language, and powers the technician assistant that answers diagnostic questions in the field.
Reviews ambiguous or conflicting sensor patterns and drafts the more detailed maintenance reports and root-cause write-ups — the tasks that benefit from careful, nuanced reasoning.
Reads technician-submitted photographs — a cracked panel, corrosion, loose wiring — and flags a potential issue for human confirmation. Never a substitute for a physical inspection.
Generates illustrative system diagrams, sensor-placement guides and training visuals — always labelled clearly, and never presented as real sensor evidence.
A resident sees a status. A technician sees a work order. An NGO sees a portfolio.
No sensor jargon, no false alarms — just whether the water is working, and a heads-up if maintenance is planned.
See the current status of the nearest pump in seconds.
Strange noise, low pressure, or visible damage — reports feed straight into the AI model as a supporting signal.
A short, plain-language notice when maintenance is scheduled — nothing alarming, nothing technical.
Illustrative figures — every deployment's real numbers depend on the pumps, sensors and communities it monitors.
Actual monitoring cost depends on sensors, connectivity and AI usage per pump — figures below are illustrative estimates.
No. The AI can only raise a recommendation. Pumps keep operating normally, and only a human technician or manager can act on an alert.
Telemetry buffers locally and syncs once the connection returns. An offline sensor is shown as "offline," never automatically treated as a pump failure.
Every prediction ships with a confidence percentage and the specific signals behind it. Pump Pulse always frames outcomes as a probability, never a certainty.
Yes. Every recommendation can be overridden, with the technician's reason logged and fed back into future model evaluation.
Yes. Access follows role-based permissions, infrastructure locations aren't exposed publicly, and all changes are recorded in an audit log.
See pump health, predicted risk and technician dispatch working together — before a community goes without water.
Monitor a pump"Asikhathali ukuthi indawo isekude kangakanani — inhloso yethu ukuqinisekisa ukuthi amanzi ayahamba, njalo. Pump Pulse was built so that no rural community wakes up to a dry tap and a pump nobody knew was failing. We watch the pumps so you don't have to find out the hard way."
A running view of what a pump's live telemetry feed looks like — sensor readings, the data pipeline, and the event log that feeds the prediction model.
Set up access for your NGO, municipality, technician team or facility.
Sign in to see live pump health, predicted maintenance risk, and the work orders waiting on your team.
Log in to your Pump Pulse account.