Research Discovery is no longer a ‘nice-to-have’. It has become an urgent necessity for Banks and other Research Providers to avoid loss of mind-share and a significant blow to their reputations with investors.
Publishers using Limeglass discovery tools to enhance existing systems are able to get their investor clients to read 8x as much relevant research content as their competitors. And that is just using traditional, ‘passive’ discovery systems such as email distribution.
Publishers using a full suite of cutting-edge discovery tools, including ‘active’ tools like advanced search and ‘analytics’ tools using Limeglass’ industry-leading rich data, can achieve an even greater boost, at least 28x greater.
These numbers are based purely on the uniquely huge size of Limeglass’ proprietary knowledge graph. While most banks have research taxonomies generally smaller than 6,000 tags, Limeglass provides a 50,000 tag taxonomy for ‘passive’ systems and access to its full 170,000 knowledge graph for ‘active’ systems.
However, those numbers do not account for even more power in the Limeglass system. The ability to query combinations of tags in both ‘passive’ and ‘active’ cases means the 8x and 28x can actually be multitudes higher. Furthermore, the fact that Limeglass tags at paragraph-level (rather than document-level) also means that investor clients get a superior experience when looking for relevant content, often being taken directly to the few nuggets they need, rather than just being shown a document in which they have to go hunting for those nuggets.
Furthermore, for anyone attempting to harness the power of Generative AI with Research Discovery, the high-impact Limeglass approach provides the perfect high-quality, auditable input into Large Language Models.