Evolv AI Begins Series of Generative AI Beta Launches That Enhance Personalization and Experimentation

Evolv AI the maker of the world’s leading intelligent digital experience optimization and personalization platform announces a series of generative AI features accessible in beta. The first new product feature in this lineup is a description-to design element, which allows businesses to instantly create complex visual web page changes from a simple text description within Evolv AI’s web editor. This enables users to increase speed to market and allows teams to focus on more strategic work, thereby amplifying human creativity and producing better outcomes.

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With the introduction of this first feature, Evolv AI aims to revolutionize the personalization and experimentation landscape by empowering businesses to own and accelerate the end-to-end process — from idea to test to true customer personalization. Looking ahead, Evolv AI has exciting plans for additional feature launches throughout the summer, aiming to provide even more powerful tools for businesses. By harnessing the power of generative AI, the company will help a range of brands and agencies achieve unprecedented levels of customer satisfaction and drive significant business growth.

“We’re incredibly excited about the potential for our new description-to-design capability, and our AI assistant to amplify creativity and simplify the process of connecting people with great experiences,” said Tyler Foster, CTO and co-founder at Evolv AI.

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Evolv AI is designing these features for creatives with more ideas than resources — those who want to do big things but don’t currently have the bandwidth to achieve their goals. Evolv AI is expanding its use across various industries and job positions responsible for personalization and experimentation efforts. By automating variant creation for experiments, businesses can increase test velocity and speed to market, allowing them to gain a competitive edge. The feature also eliminates technical and resource constraints, enabling the design and execution of complex experiments that were previously reliant on developer support.

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