Simpool Introduces AI-Based Simulation-as-a-Service for Product and Revenue Managers

Technology is evolving at a rapid pace and the digital revolution has come with all kinds of new and efficient services. Such a service is a simulation as a service.

The concept of simulation as a service is still in its infancy, but seems to have significant potential. It is an innovative approach that takes the engineering process to the virtual world and then delivers it as a technology-based service or as an engineering-as-a-service product.

What are the use cases for an AI simulation?

There are many different use cases for simulation. Some of these we see in the aviation industry. The aviation industry uses simulations to train pilots, test new aircraft and study how aircraft react in certain situations.

Simulations are also used in other fields such as healthcare, car design, firefighting and the military.

Nevertheless, there are many more applications for simulation that have yet to be explored.

How Simpool is innovating the game industry

Simpool has developed an AI-based sandbox that analyzes end-user journeys, enabling app and product developers to answer the most critical question to their product success: “What if?”. With simple server-to-server API-based integration, Simpool delivers: in-game insights, user segments and most profitable predicted configurations. Simpool gives product, revenue and user acquisition managers a competitive advantage by enabling them to gain 10x faster data insights, 100x more exploration options and 20x faster product iterations, resulting in saved time, effort and the ability to predict churn, conversion and LTV

Guy Bar Sade, co-founder and CEO of Simpool, was Director of BI & Analytics at Playtika (Nasdaq: PLTK) from 2013 to 2015 leading towards a truly data-driven company. Speaking to New York Tech Media about the value Simpool brings to product developers, “Using Simpool allows product developers to maximize their work efficiency and innovation ambitions as key barriers have been removed. Concerns and risks of damage to running applications with a faulty new variant and bottleneck development can be applied with minimal effort in Simpool’s artificial ‘sandbox’ and tested. Admittedly, results never correspond 100% to reality, but 80% is good to understand whether a strategy is good or not”.

In the interview, he also discussed the influence of sandbox optimization models on traditional A/B testing: “While AB testing is a ‘used’ strategy, I believe that predictive methods and advanced ‘What-if’ engines We can see this concept being used in the aviation world while training pilots on edge cases or even in the medical field where doctors can be trained in simulators before performing complex operations. Online space will follow this trend , and it will also enable segmentation applications, MLops space with heavy data preparation processes, which are essential to model user behavior.”

Last updated: January 3, 2022