Case Study: LPL Financial improves search accuracy with GraphAware Hume

Developing the “Single Brain” for LPL Financial with GraphAware Hume

LPL Financial, a broker-dealer, faced the challenge of building a single source of truth for its vast organizational knowledge. This "single brain" was needed to power multiple business applications and to solve specific issues, such as optimizing the search of internal documents to save time and reduce support costs. To address this, they worked with vendor GraphAware and utilized their Hume platform.

GraphAware's solution involved a four-step process with Hume: data ingestion, natural language processing, enrichment, and a planned machine learning phase. This process extracted and tagged core concepts from documents, which were then used to optimize search functionality. The implementation resulted in a significant 10% increase in search accuracy right out of the box, which translated into tremendous time and effort savings for the company and its advisors.

LPL Financial

Mayank Gupta

Senior Vice President for data