Our solutions are effective because we understand the problems.
Enabling machine learning
Most scientific progress is slowed down by “unknown unknowns”. Root cause analysis can result in weeks or months of down time. The power of AI and Machine Learning lies in its ability to find patterns to help predict outcomes, identify hidden relationships, and classify systems to amplify human intuition, the foundation of good science.
But, AI systems are only as good at the data that are used for training (“Garbage in… garbage out”). That’s why we created our platform to enable granular high-quality data to be collected and fed into our algorithm engines to help scientists and engineers amplify their efforts to turn the unknown unknowns into known knowns. Here’s what we mean:
A biotech company was experiencing inexplicable results from their pilot production runs in preparation for scale up. Whilst they checked everything they could, they still couldn’t find the root cause, resulting in weeks of schedule slippage. They had installed our Elements to continuously collect data from many of their instruments as well as their facility’s environment, so the algorithms were able to help them zero-in on the root cause by analyzing their experimental results together with all of their Element sensor data streams. The root cause? Their HVAC system was having an impact on their formulation steps that was propagating downstream to production stages. By having access to continuous data from other parts of their facility, the algorithms were able to extract the (hidden) relationship from an upstream process that was affecting the yields downstream.