Case studies

A global SaaS provider managing 30,000+ tickets per day across Tier 1 through Tier 4 was suffering not from a lack of data but from fragmentation. Support agents navigated across disconnected systems — ITSM, observability, knowledge base, CRM — and manually reconstructed context per incident. The organization implemented a contextual data layer on Arango — ingesting all relevant data into a single platform and continuously contextualizing it, creating a living context graph that the AI support agent operated against directly.

Outcomes

PSI is a global clinical research organization. Selecting the right trial sites is one of the most expensive decisions in drug development: trials can take a decade and cost hundreds of millions. The data existed already — detailed records on investigators, institutions, protocols, and historical outcomes — but it was fragmented.

PSI built SYNETIC, an AI-enabled knowledge system powered by the Arango Contextual Data Platform, unifying structured and unstructured records into one continuously maintained context graph.

“Our AI agent doesn’t just recommend trial sites — it explains why, with the data and relationships that led to the recommendation.”

— Andrei Seryi, Director of Knowledge Management and Process Improvement, PSI

Outcomes

Chapter 4 FAQs