ELIPSA AIoT ENGINE
Predict the outcome of your process before you start
Elipsa allows users to quickly and easily build predictive models to determine the quality of the production run at each step in the process, helping producers dial in the optimal recipe for their desired outcome.
Data collected from product sampling, machine settings, and IoT sensors can be combined to predict the quality of your final product.
Eliminate defects, decrease waste and increase customer satisfaction with predictive analytics.
Processing raw materials into finished goods often involves a multi-step process with many points of failure and quality degradation. The quality of this final product often dictates the price that can be charged for the product.
Utilizing machine learning, machine settings, and sensor readings can enable users to predict the quality of the final product. AI can help to optimize settings to increase final quality, decreasing costs and increasing revenue.
Understand the impact that each stage of the manufacturing process has on quality.
Optimize machine settings to ensure the highest fo quality in your final product helping to cut costs and increase customer satisfcation.
Agriculture involves many moving parts from environmental readings to soil measurements, down to plant spacing.
Elipsa enables users to easily build models taking in multiple inputs to predict the final output.
Users can utilize no-code AI to optimize their process and increase their overall yield helping to cut costs and increase revenue.
In a test use case of detecting whether products were defective in a raw material processing use case, Elipsa was able to quickly build a model that was 97% accurate in classifying output products as defective or not.
These predictions can allow organizations to optimize machine settings ahead of a production run to reduce defects thus reducing waste, saving time, and increasing quality.