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  • Predicting water quality to minimize compliance risk.
  • Managing chemical dosage to optimize costs.
  • Monitoring asset performance in real-time.
  • Inefficient resource use and unnecessary downtime.
  • Lack of predictive digital tools to optimize process changes.
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Sectors Plutoshift supports:

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Commodity
Chemicals

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Specialty
Chemicals

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Fertilizer

biopharmaceuticals sector icon

Biopharmaceuticals

cosmetic sector icon

Cosmetics & personal care products

Use Cases

1.
Chemical production process efficiency
2.
Chemical inventory management
3.
Chemical consumption at wastewater treatment plants
4.
Membrane system performance
1.
Optimize process performance through predictive modeling on equipment performance
2.
Apply custom algorithms to connect production and inventory volumes with more timely and refined views on consumption and demand
3.
Optimize dosing practices to account for chemical costs, treatment requirements and production levels
4.
Proactively monitor and enhance the sizing process of membrane systems through automated learning models

Use Cases

Chemical production process efficiency.
Optimize process performance through predictive modeling on equipment performance
Chemical inventory management.
Apply custom algorithms to connect production and inventory volumes with more timely and refined views on consumption and demand
Chemical consumption at wastewater treatment plants.
Optimize dosing practices to account for chemical costs, treatment requirements and production levels
Membrane system performance.
Proactively monitor and enhance the sizing process of membrane systems through automated learning models

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CEO Prateek Joshi talks about digital transformation in the water sector. Prateek hits on a number of important and practical points in a wide-ranging discussion on data, AI, and...

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