Rapidly Operationalize Machine Learning and AI
AI/ML is a hot technology but like the cloud a few years back, many organizations aren’t clear how to leverage it. Uncertainty is high and AI/ML requires a heterogeneous toolkit that changes often. So the uncertainty/benefits dilemma usually means no action is taken.
To solve this, our clients have turned to System Soft Technologies ML Ops practice to augment their existing applications with AI/ML seamlessly. We handle the end-to-end workflow so their data scientists can focus on creating the best data models.
Key Capabilities
Clouds Supported
AWS
Azure
Use Cases
1. Measuring Digital Marketing Effectiveness
Solution Delivery
Business relevant features created from multiple data sources
Tree-based models (Random Forest, Gradient Boosting) were built to predict sales
Models deployed On-prem. Models were updated everyday based on campaign data (spend, sales, etc.)
Outcome
The insights dashboard helped the Digital team optimize the marketing campaign and improved the effectiveness by 12%, resulting in additional sales of $3M for the campaign.
2. Improve Website Engagement
Result:
Average time spent per session increased by 220%. Sales revenue grew 4X.