A Look Under The Hood
Increase capacity without buying new equipment, running trials, or interrupting production.
Meet Your Goals
Deep learning models suggest optimal operating conditions that balance targets for production, quality and economics.
Reduce GHG emissions, energy consumption, and waste streams. Exceed expectations.
How It Works
Better Results Faster
Experimental process trials are challenging. Each trial operating point carries a risk of a process upset, and results can be difficult to evaluate.
Leverage the data you already have to improve your operations.
Our deep learning models guide you towards an optimal operating point that balances your goals for production rate, product quality and economics.
Experienced industrial engineers and data scientists support you in achieving competing goals.
- Improve capacity without downtime
- Improve product quality
- Reduce energy consumption, emissions, and effluent
- Reduce additive consumption
- Adapt to seasonal changes and aging equipment
- Adapt to changing feed and product specifications
- Adapt to new regulations
Our deep neural networks can identify trends that conventional engineering analysis can't. Interrogate our model to understand the trade-offs in your process better.