AmanziWatch listens to communal standpipes and reservoirs in rural villages, and tells your municipal team the moment a pipe bursts, a pump fails, or a reservoir is running dry — before residents go without water.
"Weekly water interruptions were most common in Mpumalanga, Limpopo, and KwaZulu-Natal."
A low-bandwidth sensor network feeds an anomaly-detection model that watches every standpipe and reservoir around the clock — and tells the right person, in plain language, the moment something is wrong.
Low-cost sensors on communal standpipes and reservoirs, communicating over LoRaWAN so they work on the low-bandwidth connectivity typical of rural sites.
Sensor readings stream into AWS IoT Core, funded through AWS Activate credits, giving the project a scalable ingestion layer from day one.
A time-series model flags leaks, pump failures, or unusually fast reservoir depletion — patterns a human checking in once a week would miss.
Plain-language alerts, generated in local languages, reach the municipal water team and community leaders via Twilio or Africa's Talking.
Two models doing two different jobs — one watching the numbers, one explaining them to people.
Isolation Forest / Azure Anomaly Detector runs continuously against flow and pressure readings, catching the statistical signature of a leak or pump failure early — not after the reservoir is already empty.
Once an anomaly is confirmed, a lightweight LLM via Azure OpenAI Service turns raw sensor deltas into a short, plain-language message in the local language of the receiving team.
AmanziWatch doesn't lock into a single vendor. Each provider is doing the thing it's genuinely best at, so the system stays cheap to run and easy to move if a municipality's procurement rules require it.
AWS IoT Core takes the raw MQTT stream from every sensor over LoRaWAN gateways, handles device authentication, and buffers readings so a patchy rural connection never loses a reading.
Azure Anomaly Detector scores every incoming flow/pressure reading in near real time. Once it flags a genuine event, Azure OpenAI Service (GPT‑4o‑mini) turns the numbers into a short alert a non-technical reader can act on.
BigQuery holds the long-term sensor history so municipalities can see trends over months, not just the last alert. Looker Studio turns that into the dashboard council officials actually open.
A pressure sensor just reports a number. It takes a model to know that number is wrong — and a second kind of model to say so in a sentence a busy municipal worker can read in five seconds, in the right language, without a data science degree.
A time-series model (Azure Anomaly Detector / Isolation Forest) trained on normal flow and pressure behaviour for each site. It doesn't need to know what a burst pipe is — only that this reading doesn't look like the others.
Handles the high-volume, low-cost job: turning a confirmed anomaly into a short, local-language SMS or WhatsApp message, fast and cheap enough to run on every single alert the system generates.
Brought in for the harder reasoning work: weekly summaries for municipal managers, distinguishing a genuine burst from a maintenance shutdown or sensor fault, and drafting the incident notes an engineer reads before rolling a truck out to a rural site.
From a standpipe in a rural village to a WhatsApp message on a municipal engineer's phone, in roughly 40 minutes.
Four short reads covering why AmanziWatch exists and what it actually costs to run.
Overslimy founder Tshegofatso Kevin Sathekge started this project after watching a village standpipe run dry for three days before anyone in the municipal office knew. AmanziWatch exists to close that gap between a pipe failing and a person finding out — turning a three-day silence into a 40-minute alert.
Stats SA's 2025 General Household Survey found 36% of Mpumalanga households, 25.9% in Limpopo, and 24.2% in KwaZulu-Natal report weekly water interruptions. SAICE estimates 40%+ of treated water is lost nationally to leaks — mostly because nobody knows a failure has started until residents complain.
Low-cost LoRaWAN sensors feed AWS IoT Core around the clock. Azure Anomaly Detector scores every reading against what "normal" looks like for that specific site. When it flags a real event, GPT‑4o‑mini writes the alert and Claude handles the reasoning-heavy work — weekly summaries and telling a genuine burst apart from routine maintenance.
Anomaly detection compute runs R335 – R1,005 a month per sensor cluster, billed on commodity Azure compute regardless of how many alerts fire. Alert generation via GPT‑4o‑mini only costs money when something actually happens: R2.51 – R6.70 per 1,000 summaries. Quiet infrastructure costs nothing extra to explain.
Every cost on this page is quoted and billed in South African rand — what a municipality sees is what it pays.
Per municipality sensor cluster, running on commodity Azure compute. Scales with the number of standpipes and reservoirs monitored.
Only billed when an anomaly actually fires — quiet infrastructure costs nothing to explain.
All prices quoted in South African rand (ZAR). Overslimy bills municipalities directly in rand — no dollar invoicing, no FX pass-through.
AmanziWatch is developed and operated by Overslimy, based in Krugersdorp, Gauteng. "Amanzi" means water in isiZulu and isiXhosa — the project exists to make sure that word doesn't become a source of anxiety for rural households.
| Registered name | Overslimy |
| Founder | Tshegofatso Kevin Sathekge |
| Company reg. no. | 2026/595757/07 |
| Tax reference no. | 9058454324 |
| Registered address | 8 Saul Jacobs Avenue, Mindalore, Krugersdorp, Gauteng, 1739 |
"AmanziWatch is going to succeed because it solves a problem South Africans feel every single week, with technology that finally makes the invisible visible. When a rural family can trust that their municipality will know about a burst pipe in minutes instead of days, we're not just fixing infrastructure — we're rebuilding the basic promise that water will be there when you turn on the tap. That trust is what secures the future for millions of South Africans, one village at a time."
| Director | Tshegofatso Kevin Sathekge |
| Role | Founder & Director, Overslimy |
| tshegofatso@overlyslime.co.za |