Slide background
Slide background
Slide background
Slide background
Slide background

By using Artificial Intelligence to augment Data Science, Ople can implement more accurate models that will result in better forecasting, proactive customer engagement, shortened sales cycles and reduced churn, all while optimizing processes to contain the high cost of data science.

Even more so, companies applying AI to data science are rapidly solving problems that could not previously be solved to identify sales opportunities, locate hidden cost savings and establish new business advantages.

Ople works with large and small data sets, detecting patterns and relationships to more accurately predict outcomes. Simply put, Ople gets better with every project and with every model it constructs.

  • Faster

    Prepare your dataset, upload it to our AI, and let it deliver the best possible model faster than any human can (in days not months).

  • Guaranteed Outcomes

    Every dataset makes Ople’s AI better. No matter how new or different the data, our AI learns and innovates on methodologies to guarantee the best possible outcome.

  • Efficient

    Focus on the business challenge, not the plumbing. With Ople, each member of your team can quickly deliver new ways for AI to transform your business instead of spending months tuning models.

  • Competitive Advantage

    Ople allows you to deliver 3-4 new models per month, while your competition’s teams are struggling to deliver 3-4 models per year. This speed of execution defines competitive advantage.

  • Simplified

    Once you’ve prepared your data, you are done! Ople’s AI automates and simplifies complex model building, deployment, scaling and monitoring your models, freeing your team to tackle the next challenge.

Simplified Data Preparation

Ople’s models are trained using smaller data sets.

Faster, More Accurate Predictions

Get real-time forecasts and insights while the model is still training.

Automated Integration and Optimization

Models are immediately available for integration into production applications and continuously optimized after deployment.