Quickplay and Google Cloud partner on generative AI

Cloud-based OTT technology outfit, Quickplay has teamed up with Google Cloud to utilise generative AI to create new opportunities for consumer engagement and monetisation for the media and entertainment industry.

The Quickplay platform which encompasses of single tenant, cloud-native, microservices, and API-driven – architecture was combined with Google Cloud Vertex AI. According to the company, using simple API integrations, the Quickplay platform immediately enables multiple media and customer use cases, including deep metadata, content discovery, personalisation, content creation, process automation, and multi-channel monetisation.

Quickplay is partnering with Google Cloud to spearhead access to new AI capabilities that can efficiently accelerate time-to-market to deliver targeted AI solutions, maximised against a client specific go-to-market strategy. In addition, to create bespoke features and capabilities without the cost and cycles of custom development. Lastly, to implement A/B testing to evaluate outcomes and optimize consumer engagement and monetisation.

The partnership aims to open opportunities that can improve consumer satisfaction, with the following such as augmented ad campaigns; optimal ad insertion points; deep metadata for enhanced discovery, recommendations, automatic clips/highlights generation, multiple length synopses, subtitle translations and conversational content discovery.

Paul Pastor, chief business officer and co-founder of Quickplay said the integration of Quickplay’s platform, with Google Cloud Vertex AI, will demonstrate how the use of AI can “accelerate the pace of innovation and deliver new revenue opportunities.”

Juan Martin, CTO and co-founder of Quickplay added, “When we designed our cloud-native architecture, it was to take advantage of emerging  technology, like generative AI. By giving our customers access to AI marketplaces such as Google Vertex AI, we’re accelerating innovation to address customers’ most pressing concerns – revenue maximization, churn reduction, metadata enhancement, user engagement and more – using AI models that have a continuous improvement cycle we aim to drive continued business improvement.”