We make waste a more valuable resource through AI-based waste quality management

We are a pioneer company in automated assessment of unstructured waste streams in high volumes: Our technology continuously analyzes and quantifies complex waste streams, enabling impurity detection, value chain traceability, and more efficient plant operations.

With our AI-based solution we bring transparency into unstructured waste streams: Identification of impurities, temperature hot-spots, emissions, calorific value, validation of waste classification code and characteristics such as homogeneity or dustiness combined with supplier traceability and automated reports.

Optimization of the plant process chain through transparency of the material flow

Our solutions - WasteAnt Our solutions - WasteAnt

Material acceptance

  • Impurity detection
  • Material characteristics
  • Validation of waste classification code
  • Temperature monitoring
  • Producer statistics
  • Documentation

Conveyor belt

  • Impurity detection with emergency stop
  • Calorific value prediction
  • Emission prediction (e.g. HCl)

Bunker management

  • Homogeneity evaluation and recommendations

Incineration forecasts

  • Calorific value prediction
  • Emission prediction (e.g. HCl)

In a typical Waste–to–Energy plant, we can

decrease - WasteAnt

decrease
plant operating costs

Avoid unexpected downtimes through impurity detection

Less maintenance effort through impurity detection

Reduction of delivery inspection time by 95% through automated delivery analysis

Reduction in the use of fossil fuels and cleaning material through calorific value forecasts

reduce - WasteAnt

reduce
emissions

Reduction in the use of fossil fuels for incineration

Avoidance of emission peaks through better material homogenization

increase - WasteAnt

increase
electricity outputs

Incineration closer to optimal efficiency through AI-supported material selection

Higher material incineration volume through fewer downtimes

Potential annual financial benefit of the solution per plant: 0,5-4 M €

Our system learns with every delivery and already delivers decisive added value

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tons of analyzed waste

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boxes installed in plants

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material deliveries analyzed

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for temperature and impurity detection

Our projects

swb - Our pilot partners - WasteAnt
swb

At SWB's MKK, all acceptance gates are equipped with our material analysis system. Systems for material homogenization and calorific value prediction are active in the bunker and at the drop chute.

Neew Energy from Waste - Our pilot partners - WasteAnt
Neew Energy from Waste

For NEEW Ventures, we set up a system for predicting calorific values in an EEW plant.

hkw blumenthal - Our pilot partners - WasteAnt
hkw blumenthal

At the Blumenthal HKW, a WasteAnt system analyzes the material on the conveyor belt for rigid long parts and their composition. An automatic emergency stop prevents drop chute blockages, while steam mass and HCL prediction reduce anomalies during operation.

GML - Our pilot partners - WasteAnt
GML

With GML, the WasteAnt system indicates impurities in the drop chute to prevent them from entering the drop chute.

AMK Iserlohn - Our pilot partners - WasteAnt
AMK Iserlohn

At the AMK Iserlohn, a material analysis is carried out with impurity detection at the acceptance control, calorific value predictions at the drop chute and the identification of chlorine and sulphur sources to optimize exhaust gas and wash water treatment.

AGR Herten - Our pilot partners - WasteAnt
AGR Herten

At AGR Herten, our system was installed at the acceptance control to carry out a material analysis to examine the waste quality and detect impurities.

Our supporters

Hightech Inkubator Oldenburg - WasteAnt
Kraftwerk City Accelerator Bremen - WasteAnt
Bremen Startups - WasteAnt
BAFA - WasteAnt
Equihub - WasteAnt
Nvidia Inception Program - WasteAnt
akquinet - WasteAnt
BAB Die Förderbank - WasteAnt
Die Senatorin für Wirtschaft, Häfen und Transformation - WasteAnt
VKU - WasteAnt
German Accelerator - WasteAnt
Winner Badge Jury Award 2024 - WasteAnt

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