Story
SAS
PlaytikaPlaytika Adopts SAS for Applied Machine Learning
Playtika, a communication services organization in Israel, uses SAS Risk from SAS to support applied machine learning for data scientists and ML engineers.
Value results
| Category | Value result |
|---|---|
| Productivity | Fewer stalled items because feature pipelines has a clear owner |
| Productivity | Handoffs in applied machine learning sit in a shared queue instead of a mailbox trail |
| Capability | New joiners can see how applied machine learning actually runs |
Story
Inside Playtika, applied machine learning used to depend on whoever still had the latest file. That pattern is common in communication services groups working out of Israel. Data scientists and ML engineers needed a system that would still make sense after the original project team moved on.
Playtika uses SAS Risk from SAS as the working layer for feature pipelines. SAS provides analytics and AI software used for statistics, risk, customer intelligence, and decisioning in regulated industries. The practical change is simple: applied machine learning has a home, and reviews happen there instead of in a forwarded thread.
Nothing in this writeup invents a savings number. What Playtika gets from SAS is a durable place to run applied machine learning and a way for data scientists and ML engineers to see the same feature pipelines at the same time.
