Use Case

AI Product Deployment: User Experiences in the Age of AI

Deploy AI-driven applications to deliver seamless, interactive experiences revolutionized by advanced AI and intuitive natural language search.

AI-Powered Streaming Platform

Streaming platforms leverage AI to deliver contextualized content recommendations and dynamic, interactive experiences, significantly enriching viewer engagement.

How it works

Data Graphs connects user behavior with relevant assets to deliver hyper-personalized content recommendations, optimizing streaming experiences and driving superior engagement and retention.

Example

A streaming service leverages Data Graphs to deliver AI-driven recommendations, offering personalized content based on viewing history and preferences while incorporating interactive elements.

AI-Powered E-Commerce Platform

E-commerce platforms leverage AI to personalize product recommendations, enhance customer experiences, and optimize pricing strategies.

How it works

Data Graphs integrates product data, user preferences, and purchase history to deliver personalized recommendations and enable dynamic pricing automation, driving increased sales and enhanced customer satisfaction.

Example

An e-commerce platform can leverage Data Graphs for AI-driven product recommendations, precisely tailored to each user's preferences and behavior, ultimately boosting sales.

AI-Powered Healthcare Systems

Healthcare organizations leverage AI to enhance patient care, optimize operations, and improve the accuracy of clinical decision-making.

How it works

Data Graphs integrates clinical data, patient records, and medical literature to drive AI-powered solutions, enabling personalized treatment plans, risk identification, and automation of routine tasks.

Example

A healthcare provider uses Data Graphs to analyze patient data, deliver personalized treatment recommendations, and proactively identify potential complications.

AI and Natural Language for Data Discovery

Utilize natural language search across various applications and data sources to streamline and transform data discovery.

How it works

Data Graphs interprets natural language queries, connecting diverse data sources (DAMs, MAMs, PIMs, documents, wikis, databases) to deliver relevant results.

Example

A search query such as "classic Westerns pre-1960 vs. post-1970" returns relevant videos, trailers, synopses, and credits, providing a comprehensive view.

Semantic Knowledge Hubs for Enhanced Search

Semantic search greatly enhances large enterprises by delivering context-aware results across documents, customer data, product assets, and project files, thereby improving decision-making and productivity.

How it works

Data Graphs organize and enhance knowledge base content, enabling powerful semantic search. Its AI understands natural language and provides highly relevant answers.

Example

A retail company can leverage Data Graphs to optimize its knowledge hub, allowing employees and customers to easily find accurate product information, leading to improved customer satisfaction and reduced support time.