Advanced AI features: foundational to The Retail Media CloudTM

Kai, Kevel Artificial Intelligence, is our suite of advanced AI technologies that power The Retail Media CloudTM

Boost fill-rates
Real-time predictions
Real-time predictions
Boost fill-rates
Intelligent pacing
Intelligent pacing
Custom Relevancy
Custom Relevancy
Maximise yield
Maximise yield
Goal-based segments
Goal-based segments
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Kai powers key features in the Retail Media CloudTM. In Kevel Ad Server, it informs forecasting, pacing, decisioning, and custom relevancy to give retailers smarter results. In Kevel Audience, Kai’s advanced machine learning models provide user-level predictions and the AI-segment builder. With Kai, retailers promote the best advertiser and user experience and capture more ad spend from competitors.

Kevel Ad Server
Kevel Artificial Intelligence Type

in Kevel Ad Server

Our full suite of composable ad serving APIs to power ad decisioning, campaign management, reporting, and catalog ingestion. Work via API or use our intuitive UI to power all of your owned inventory.

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Decision API

AI is at the heart of Kevel’s decision engine. The AI decision engine uses machine learning to intelligently balance between advertiser, retailer, and user priorities. Shoppers always get highly relevant ads that still benefit the retailer and advertiser.
Kevel Artificial Intelligence Ad Server

Forecast

Kevel Forecast uses advanced machine learning simulations to generate insights on available inventory for current flights and future flight delivery performance. This helps sell, plan, and optimize while boosting sell-through rates, fill-rates, and ad operations efficiency.
Kai Ad Server Forecast

Pacing

Kevel enhances the traditional pacing approach with a feed-forward input produced with machine learning. Pacing looks at historical decision and event details as well as trends and predictions regarding an ad’s likely future performance, providing a balanced flight delivery.
Kevel Artificial Intelligence Ad Server

Custom Relevancy

With Custom Relevancy retailers can BYOM: bring your own model. Retailers know their customers best and typically have advanced AI/ML models for understanding them. Now, retailers can supply their own models and use them immediately as an ad is selected.
Kevel Artificial Intelligence Ad Server

Led by an expert team

Tim Ewald

Tim Ewald

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Chief Technology Officer

Tim is Kevel’s CTO and has spent the last 30 years building distributed software systems to solve problems in a wide range of domains, including image analysis, content management, video processing, databases, and ad tech. He brings his experience as an engineer, architect, and engineering manager to Kevel, where he is responsible for the entire cloud platform. Tim is an author and conference speaker, who holds a Bachelor's in Computer Science from Hampshire College. Outside of the office, he builds furniture using hand tools.

Paulo Cunha

Paulo Cunha

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VP of Product

Paulo has been building products for the digital marketing and advertising industry for over 18 years. After completing his BSc in Computing from London Met, he started his career developing products at companies such as Acxiom and Wunderloop – Europe’s first behavioral targeting technology. Paulo later founded ShiftForward, where he launched products such as the Private CDP and the Ad Forecaster and served as CEO, completing its exit to Velocidi in 2018 and later to Kevel in 2022. Paulo also helps tech startups as a board advisor and as a mentor in the Founders Founders community which he helped create in Porto, Portugal.

Paul DeGrandis

Paul De Grandis

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Innovation Leader

Paul is an information systems and innovation leader. He helps organizations use their knowledge and assets to gain competitive advantages through novel, strategic innovations and creative culture driven by a human-centered, results-oriented approach. Working with startups and Fortune 500 companies alike, Paul envisions and executes new technical strategies, unlocking value with next-generation information systems. He is a member of ACM and W3C Advisory Committee (Kevel’s AC Rep), and participates in the ACM Global Practitioner Advisory Board and W3C groups. His open source contributions include Clojure, ClojureScript, Pedestal, PyPy and more.

Richard Carter

Richard Carter

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Principal Data Scientist

Richard has over 20 years experience applying mathematics, statistics and machine learning to solve business problems. His career has spanned financial services, algorithmic trading, consultancy and advertising, working for stellar companies such as Goldman Sachs and Amazon. In his role as Principal Data Scientist he is responsible for bringing innovative machine learning-based features to Kevel's Kai platform. Richard holds a PhD in Machine Learning from the University of Edinburgh.

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