Overview
Liquisens turns existing water data into real-time intelligence by applying AI on top of current monitoring systems. The platform helps industrial and municipal operators across process water and wastewater detect events early, ensure compliance, and avoid costly shutdowns by transforming water management from reactive to predictive. It combines real-time monitoring, predictive analytics, and continuous optimization, connecting to existing sensors or deploying IoT tools to monitor water quality parameters.
Key people
In the news
- Meet the Team: Guillaume Hert Guillaume is Business Developer France at Liquisens. France has been part of the Liquisens story from the start. A municipal treatment plant in Le Mans where real process data trained our models. Pollutec in Lyon. CGLE in Rennes. The biofilm and deposits day in Nancy. Guillaume’s job is to turn that presence into lasting work with French industries and utilities. Conversations with plant managers, process engineers and decision makers who want to know what their existing data could tell them before
- Your plant data builds the model. The model should belong to you. Before a predictive water project begins, two questions deserve a clear answer: who owns the data, and what happens to the model once it is delivered? With Liquisens Predict, customers retain ownership of their data throughout the engagement. The delivered plant model becomes their property at handover. This matters because the model reflects something specific: how your plant behaves. Its operating history, process conditions, and relationship between treatment
- Liquisens Insights, Edition 8 is out Predictive optimisation rests on an assumption that is rarely stated: that the plant already generates the data a model can learn from. Many plants do not. There is a PLC, an HMI panel, and someone who writes down the values once a week. Chemical consumption is known from purchasing records. Dosing per hour is not. The usual conclusion is that predictive tools are for mature plants and everyone else has to wait. We think that conclusion is wrong. This edition explains why the least digitalised
- Livestock farms use air scrubbers to remove ammonia from the air before it leaves the barn. But who keeps an eye on the scrubber? That’s where Liquisens, GF (Georg Fischer) and Crodeon Technologies team up: Liquisens manages the project, GF measures the flow, and our Reporter® sends the data to the cloud. Farmers can check the measurements from anywhere, supporting mandatory monitoring with minimal changes to the installation and no added pressure loss. Clean air. Clear data. Happy teamwork. Good job Steven De Schrijver, Chiel
- Every plant gets its own model. This is how it gets built. Step one, ingestion. SCADA data, lab measurements, weather. Weather matters more than most people expect, because rainfall changes influent long before anyone sees it in a result. Step two, preparation. Cleaning, aggregation, alignment. Unglamorous, and the step that decides most outcomes. A lab result timestamped when it was entered rather than when the sample was taken will quietly wreck a model. Step three, construction. Which inputs matter, over which time windows, and
- We are hiring a Technical Implementation and Data Specialist for our projects in Flanders. Air scrubbers in agriculture, wastewater treatment plants, industrial installations. An external installer usually does the physical work. You prepare it, coordinate with the customer and the supplier, follow the execution, and then commission the system technically and digitally. Sensors, wiring, power, communication, gateways, alarms, data connections. Then you open your laptop and ask the questions that decide whether any of it is
- Dinsdag 22 september om 15u geef ik samen met Bardia Ghazanfari een korte webinar over hoe we bij Liquisens plantdata omzetten in bruikbare voorspellingen. Veel water- en afvalwaterinstallaties beschikken vandaag al over heel wat data: SCADA, laboresultaten, procesparameters, weersgegevens, … De uitdaging is vooral om daar informatie van te maken waarmee je operationeel iets kunt doen. Tijdens deze sessie tonen we stap voor stap hoe we van die bestaande data naar een plantspecifiek voorspellend model gaan — en hoe zo’n model
- Liquisens Webinar: from plant data to a working prediction On Tuesday 22 September at 15:00 CEST, Steven De Schrijver, CTO and co-founder of Liquisens, and Bardia Ghazanfari, Water System and Data Engineer, host a 30-minute online session. Most plants still learn about a water quality deviation after it has happened. The standard compensation is a safety margin: extra chemicals, extra energy, extra reporting effort, carried every day of the year. The session shows how the data a plant already produces — SCADA, lab results, weather
Alumni
- PSteven SchrijverCEO & co-founder
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