Qloo is an AI-powered cultural intelligence and consumer taste prediction platform that helps businesses understand audience preferences, personalize recommendations, and improve marketing decisions. The platform analyzes more than 600 million structured cultural entities and over 30 trillion cross-domain relationships and behavioral signals across entertainment, dining, travel, retail, fashion, and other industries. Its proprietary Taste AI technology identifies connections between consumer interests, brands, products, locations, and cultural experiences without requiring personally identifiable information. Qloo provides audience intelligence, cultural data enrichment, personalized recommendations, geographic insights, and AI agent grounding through its API and data services. Businesses can use the platform to develop recommendation engines, identify brand partnerships, optimize marketing campaigns, and tailor products or experiences to specific audiences. Qloo also supports integration with large language models, customer data platforms, data warehouses, and enterprise applications to deliver privacy-focused personalization at scale.
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Papirfly is a SaaS leader in Digital Asset Management (DAM) and Templated Content Creation software. Our solutions help global brands organize digital assets, create on-brand marketing content, and distribute it across every channel — from video and social media to web and print.
Serving more than 1 million users across over 1,500 organizations, including Mercedes-Benz, Mondelez, and Goldman Sachs, Papirfly enables marketing teams to maintain brand consistency, scale content creation, and improve creative efficiency across global teams.
Following the 2021 merger of Papirfly and Brandmaster, the Papirfly Group expanded to include Papirfly, Keepeek, Brandpad, and Adgistics — bringing together decades of expertise in Digital Asset Management, brand portals, and on-brand content creation to help organizations activate their brand with clarity and consistency.
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Predibase
Declarative machine learning systems provide the best of flexibility and simplicity to enable the fastest-way to operationalize state-of-the-art models. Users focus on specifying the “what”, and the system figures out the “how”. Start with smart defaults, but iterate on parameters as much as you’d like down to the level of code. Our team pioneered declarative machine learning systems in industry, with Ludwig at Uber and Overton at Apple. Choose from our menu of prebuilt data connectors that support your databases, data warehouses, lakehouses, and object storage. Train state-of-the-art deep learning models without the pain of managing infrastructure. Automated Machine Learning that strikes the balance of flexibility and control, all in a declarative fashion. With a declarative approach, finally train and deploy models as quickly as you want.
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