Automated Machine Learning for Predictive Modeling
Burke Powers | Founder & Managing Director RevealWhy
“With Auger.AI, we have finally found a partner that can deliver everything autoML has promised but struggled to deliver for years. With it, we have an easily developed, highly capable, and low cost way of delivering world-class results. This will become a significant differentiator and advantage for us in the marketplace.”
Igor Palant | Sr. Manager, Release Engineering
"Omnicell used Auger.AI to build predictive models to optimize reorder points for drug reordering for their medication dispensing cabinets." Omnicell is leading a radical transformation of medication management through their vision of the Autonomous Pharmacy.”
Devin Holmberg, CEO. YTZ.com
"At YTZ we had tried many algorithms and hyperparameters to try to get acceptable accuracy in our machine learning project. Auger’s smart search allowed us to quickly find the best predictive model for our data. That combined with the ability to affordably scale up and down our cluster to meet the needs of our data size make Auger an integral part of our machine learning process."
Paul Mendoza | CEO/Founder
“For SigParser we had used a regressor model to find email signature patterns in email bodies. Without Auger the best we managed to achieve was R2 of 0.72 with manual tuning and months of effort. Within an hour of signing up for Auger, it had discovered a better model and tuned hyperparameters to achieve a 0.87 R2. That is a huge improvement! Auger will now be an essential part of our model development process.”
Peter Rabover | CEO and Founder | Artko Capital
"I used to painstakingly build linear regression models to estimate performance. Auger.AI picks more advanced algorithms and tunes their hyperparameters, letting me focus on being a true analyst."
Ramneek Bhasin | Cofounder & President
"Predicting demand and supply for contingent employees is a key success factor for our labor marketplace business. Auger.AI built accurate models for us within hours, allowing our developers to focus on the core product, and not on choosing models and hand-tuning them, something we could have spent months doing.”