Our Services

We offer a variety of services based on artificial intelligence to improve water management


Forecasting the pipes that are the most vulnerable to breakage in your city’s water distribution network. Up to 10x more accurate than the age-based models.

Every day, approximately 850 water mains break in North America, costing over $3 billion per year to repair. Infrastructure continues to age and the inadequate replacement plans continues to impact citizens and their communities daily. Water infrastructure rehabilitation costs are expected to increase in the coming decades as water networks deteriorate, and each unexpected pipe failure comes with a high economic and environmental impact.

We work in collaboration with city managers to optimize their replacement activities and to better estimate the long-term budgetary needs for the maintenance of the water distribution network. InteliPipes is an AI-based algorithm that can be trained with the water network data of a municipality to help them identify at-risk pipes before they break. Our model uses the historical data of your city’s water network to learn the complex relationships between the different variables that can contribute to water main pipe breaks.


Our InteliFlow service provides flow forecasts for wastewater pipes up to 3 hours in advance.

In 2021, 30% of wastewater pipes in Canada were in fair or worse condition. Poor sewer conditions have a direct impact on the environment and public health. Indeed, during heavy rainfall, large quantities of water are sent into the wastewater systems by infiltration and by collection due to the loss of waterproofing. This water can rise in buildings, causing flooding in basements and lower areas of the city, or be discharged untreated into the environment in the case of combined sewer overflows. New models developed by several firms are based on flow meter data in the sewer system. However, these models do not incorporate the impact of snowmelt or real-time precipitation data.

InteliFlow relies on an artificial intelligence algorithm and real-time data from precipitation and multiple flow meters strategically located in the wastewater collection system to estimate the flow in wastewater pipes up to three hours in advance. Flow Intelligence includes the effect of snowmelt and heavy precipitation.

These accurate, real-time, short-term forecasts in the wastewater system can be used by municipalities to develop preventative measures to control basement flooding where possible, in addition to preventing untreated wastewater discharges into the environment.


Forecasting real time water quality advisories that are 90% more accurate on average.

Every year, billions of liters of untreated sewage water are poured into watersheds potentially endangering the health of citizens. The traditional water quality measurement method requires a technician to take a sample and then bring it back to the lab for analysis. Then estimating water quality requires an incubation time of ± 24 hours. By using these methods, beaches are closed too late – the day after a peak of contamination – putting swimmers at risk.

We work in collaboration with public health and environmental management organizations to help them adapt a proactive approach to water management. InteliSwim is based on an Artificial Intelligence algorithm to reliably estimate microbial contamination (i.e. Escherichia coli and Enterococci) in beach water. Our model uses historical data to learn the complex relationships between the different variables affecting water quality. Once the model is adapted to the beaches within a jurisdiction, InteliSwim can determine in real time if the concentration of any fecal indicator in the water is higher than the acceptable standard for swimming.


Alert by text message when the established criterion is exceeded and when the system returns to normal.

Daily email with the InteliSwim prediction and a graph of predictions for the last 7 days and the next 3 days.

Acces to a Web Interface with time predictions and forecasts for the next 3 days.