2 Integrations with Jellyfish

View a list of Jellyfish integrations and software that integrates with Jellyfish below. Compare the best Jellyfish integrations as well as features, ratings, user reviews, and pricing of software that integrates with Jellyfish. Here are the current Jellyfish integrations in 2026:

  • 1
    Square POS
    Square POS is a simple and intuitive point-of-sale (POS) solution that delivers a robust set of tools for sales tracking, inventory, online payment processing, digital receipts, and analytics. Available for Android and iOS devices, Square POS provides a recording of transactions offline by storing data locally and then automatically syncing all information when their is an Internet connection. Additionally, Square POS enables users to seamlessly manage details, such as names, prices, and quantities and provides features such as a barcode scanner, discounts, credit card processing, gift cards, refunds, and more. Whether or not your business has a brick-and-mortar location, building a robust online presence can help you engage customers from a distance. Square’s online solutions work with any of the above point-of-sale systems, or you can use them on your own. We give you the tools to create thumb-stopping, compelling, and on-brand ads that perform.
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  • 2
    Google Cloud Recommendations AI
    Earn your customers’ trust and loyalty by proving how well you understand them. Google has spent years delivering recommended content across flagship properties such as Google Ads, Google Search, and YouTube. Recommendations AI draws on that experience and expertise in machine learning to deliver personalized recommendations that suit each customer’s tastes and preferences across all your touchpoints. Give customers more of what they love. No need to preprocess data, train or hyper-tune machine learning models, load balance, or manually provision your infrastructure to handle unpredictable traffic spikes. We do it all for you automatically. Take advantage of Google's expertise in recommendations, powered by state-of-the-art machine learning models. They can correct for bias and seasonality and excel in scenarios with long-tail products and cold-start users and items. Integrate data, manage models, serve recommendations, and monitor performance.
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