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sitecore — independent third-party profile of a public API surface, by API Evangelist. Sitecore is a global digital experience platform that combines content management, marketing automation, e-commerce, customer insight, and personalization to help brands deliver personalized customer experiences.
Wunderkind — independent third-party profile of a public API surface, by API Evangelist. Wunderkind (formerly BounceX) is a performance marketing and identity resolution platform that turns anonymous website and mobile-app traffic into triggered, one-to-one email and text messages.
Snowplow — independent third-party profile of a public API surface, by API Evangelist. Snowplow is a behavioral data platform that enables organizations to collect, process, and model granular event-level data from web, mobile, and server-side sources, providing a data pipeline for analytics and AI use cases. The platform uses a schema-first approa
Customer.io — independent third-party profile of a public API surface, by API Evangelist. Customer.io is a customer engagement platform that combines a customer data platform, marketing automation, and messaging delivery to send behavior-triggered email, push, SMS, and in-app messages.
Find your real patterns in your own data — chat exports, AI transcripts, app history — then change one thing and measure whether it moved. Most of it is safeguards.
Curated list: foundation models of human behavior — models of people trained on behavioral traces (event logs, life trajectories, transactions) whose representations transfer across tasks
The First Audience — A Cognitive Cinema film where AI observes the audience in real-time and generates a unique narrative per viewer. No two screenings are the same.
Data-driven analysis combining Google Play market data and EU28 sustainability behavior to explore the potential of GreenGap, an app for greener daily habits. | Analisi di mercato e comportamentale per valutare GreenGap, un'app pensata per trasformare la sostenibilità in azioni quotidiane.
Longitudinal mixed‑effects analysis of a 155‑child autism cohort examining predictors of Vineland Socialization Age Equivalent (VSAE). Built models with random intercepts/slopes, evaluated language, diagnosis, race, and age interactions, and assessed missing‑data impact on inference. Mixed‑effects modeling of autism trajectories.
AI-powered qualitative coding of behavioral data. Transform, translate, describe, and evaluate textual data with single-model or multi-model consensus verification.