Rigid databases missed nuance in feedback. Graph-grounded AI now surfaces hidden trends and cuts schema rewrite time by 90%.
A Swedish technology agency serves the world’s largest brands, tasked with decoding complex consumer behavior signals from massive volumes of online feedback.
Traditional relational databases could not distinguish nuances in unstructured reviews, where a five-star rating might praise a purchase experience...
“It’s flabbergasting. All these people are talking about you, talking about your competitors, and you spend endless hours trying to analyze the signal behind the feedback.”
Creator commerce platform for building online shops and selling products.
Graph database and analytics platform for enterprise data relationships.
Related implementations across industries and use cases
Free-text comments were impossible to analyze at scale. Gen AI now summarizes trends and automates follow-ups, driving 3x more insights.
Manual tagging bottlenecked insights. AI now auto-clusters feedback and answers queries, cutting hours of analysis from every project.
Rigid databases choked on unstructured logs. Graph-based AI now maps complex networks, cutting analyst workload by 50%.
Engineers manually correlated alerts across systems. AI agents now diagnose issues and suggest fixes, cutting recovery time by 35%.
Minor edits required days of crew coordination. Now, staff use avatars to modify dialogue and translate languages instantly.
Lab supply orders were handwritten in notebooks. Digital ordering now takes seconds, saving 30,000 hours for research annually.
Experts spent 15 minutes pulling data from scattered systems. Natural language prompts now generate detailed reports instantly.