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Pallon AG (Zürich, Switzerland)Pallon
Swiss service that codes your sewer inspection footage with AI according to DIN EN 13508-2, DWA-M 149-2 or NASSCO, for pipes and manholes; results on average arrive within a week.
Shared spot11of 13 professional tools with a GDPR profileOur summary of what the provider itself publishes about your data: whether the data is held in the EU (2 points), whether there is a certification or GDPR guarantee (1) and whether the provider is established in the NL or the EU (1). 3 or 4 points is Strong, 2 Good, 1 Limited, 0 Unknown. How we measure in water management
GDPR: Unknown
- Provider based outside the EU
Priceprice on request (based on usage)based on usage (per inspected pipe length or number of wells), monthly or annual; quote on request
Free trialYes
Based inZürich, SwitzerlandOutside the EU
ModelNot publicno language model; proprietary deep neural networks and 3D vision that recognise more than 300 damage classes. Data encrypted and hosted in certified data centres, not shared with third parties (according to the provider); hosting location and own certification not published. Swiss company (outside the EU, but covered by an adequacy decision).
Last checked: 6 November 2026 · How we check
Is this your tool? Fill in missing detailsWhat it does
Automatic damage coding for sewers and manholesUpload inspection video, result in web app
Share results via a link
Pan-tilt and side-scan cameras
EN 13508-2, DWA-M 149-2 and NASSCO PACP/MACP
Export as ISYBAU XML, DWA-M 150 and VSA-KEK
Rehab Planning (early access)Comparable in water management
InfoTileson request
SIWA Leak Finderon request
QatiumQ-one and Q-plus per month on the p…
Aquasuiteon request
WISKIon request
HULOEssential €29,000/year (500 km ne…Pallon compared
Underlying model
GDPR check for water management no language model; proprietary deep neural networks and 3D vision that recognise more than 300 damage classes. Data encrypted and hosted in certified data centres, not shared with third parties (according to the provider); hosting location and own certification not published. Swiss company (outside the EU, but covered by an adequacy decision). Many tools build on a large model from, for example, OpenAI or Anthropic. If in doubt, ask for the data processing agreement: it states where your data goes.
Questions about Pallon
- Which AI model does Pallon use?
- The maker of Pallon does not publish which AI model is underneath. No language model; proprietary deep neural networks and 3D vision that recognise more than 300 damage classes. Data encrypted and hosted in certified data centres, not shared with third parties (according to the provider); hosting location and own certification not published. Swiss company (outside the EU, but covered by an adequacy decision).
- How much does Pallon cost?
- Pay per use (per inspected length or number of manholes), monthly or yearly; quote on request. Check the current price on the provider's website; rates often change.
- Who is Pallon for?
- Pallon is aimed at water management and construction & installation. It fits work such as leak detection and water loss: spotting deviations in pressure, flow and sound in the pipe network, forecasting rainfall, water levels, drought and flow to pumping stations and treatment plants, assets and treatment: predicting pump faults and adjusting processes with AI settings.
- What should I look out for with AI in water management?
- Water management is critical infrastructure: water boards and drinking water companies fall under the NIS2 rules (in the Netherlands, the Cyber Security Act), and an AI system that runs as a safety component in water management may count as high risk under the AI Act. So ask about certification, data storage and who keeps control during an outage. HULO is ISO 27001 certified, holds the SC30 NIS2 mark, stores data in the client's region and does not train on client data. TaKaDu (Spain) is ISO 27001 certified. KISTERS WISKI can run on-premise. With many other providers, such as Qatium, Siemens and FIDO Tech, the hosting location is not publicly stated: record it in the data processing agreement. Personal data mainly sits in consumption data from smart water meters; keep it separate from network data where possible.
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