Key points in your in-house research can be missed amongst the information overload
Manual document tagging is subjective which causes inconsistencies
Inconsistent document tagging leads to sub-optimal distribution to clients
Sales and clients struggle to find articles and maximise the power of the research
Limeglass smart-tagging and proprietary cross-asset and macro taxonomy enable internal and external users to quickly find exactly what they need, maximising the value of your research assets
Limeglass is a powerful tool that enables you to customise your in-house research to directly meet your clients’ requirements through detailed analytics
Limeglass provides you with flexible APIs and intuitive client user interfaces
Pre-publication
Automates & adds consistency to the pre-publication document tagging process which can be integrated into existing editorial systems.
Post-publication
Allows for powerful integration of Research Atomisation™ capabilities to enhance existing distribution, consumption & execution platforms.
Post-publication
Provides an out-of-the-box web portal for sales desks allowing instant access to specific thematic paragraphs across all asset classes & macro topics.
Search Engine Research Optimiser
Supercharges your existing search engine & AI retrieval processes for financial research content. Integrates the Limeglass Knowledge Graph to ensure far more accurate & time relevant AI results.
AI Chat Bot for Research
Integrates a research optimised AI Chat Bot component into your own solutions. Produces Extractive and/or Generative AI answers powered by the Limeglass Research Discovery Solution.
Provides consistent automated pre-published document tagging
Smoothly integrate into existing editorial systems
Limeglass ContentAPI is a REST API for interacting with post-publication research
Content Metrics provide granular analytics
Surface documents & paragraphs discussing specific financial themes
Document tags & metrics can be stored in your own search index
Provides an out-of-the-box web portal for sales desks allowing instant access to specific thematic paragraphs
Sales + In-house Research = Reputation => Trusted Advisor
Provide you sales teams with immediate access to granular cross-asset & macro themes
Improve the Quality of Search & AI Retrieval Results
Tuning search engines to work effectively with investment research or other financial content is a significant and often underestimated challenge.
Despite using a top-quality search engine, adhering to best practices, and embracing advanced methods like semantic search, chunking, and vector embeddings, search engine results often still fall short.
At Limeglass, we are the financial content discovery technology experts, and understand that an effective solution only comes from overcoming the core challenges:
With the advent of GenAI, LLMs, and in particular Retrieval Augmented Generation (RAG) – the search retrieval quality has never been more important, it is the biggest factor impacting the quality of an LLMs output.
Limeglass Fusion Search for AI is designed to tackle the challenges of searching investment research and more.
By integrating the power of Graph and Hybrid Search into existing search engines and leveraging the Limeglass Knowledge Graph of over 200,000 topics, it achieves substantially better results in clients’ tests and benchmarks.
Fusion Search for AI provides two primary API components that enhance the existing search stack:
Pre-processes financial research content before index ingestion.
Fusion Search for AI Index Pre-Processor API ensures deep granular labeling, advanced contextual chunking and metrics at both document and chunk levels, resulting in standardized metadata across all content ingested.
Providing a detailed and consistent indexing of content, while supplementing the publisher’s own metadata extensions and RIXML files (which can have variable quality).
Interprets the user’s search / prompt to enhance the search engine query.
The Fusion Search for AI Query Parser API interprets the context of the question using the Limeglass Knowledge Graph. Generating Graph / Hybrid powered search queries, including rich metadata to ensure more accurate retrieval from the index.
Providing more accurate search results
If the content in your search engine index is suboptimal, any results will be disappointing
Fusion Search for AI:
Ensuring more accurate retrieval
Fusion Query Parser parses the original query adding metadata to ensure more accurate retrieval
Provides Extractive and/or Generative AI answers
Emerging GenAI technologies have the potential to revolutionise investment research, but the risk of misleading answers and hallucinations has caused anxiety among publishers worldwide.
Increasing the quality of retrieval and providing the author’s actual sentences alongside the generative answer in an ‘Extractive’ way allows for fact-checking with the source content and maintains the feedback loop.
To ensure effective results, you need a highly tuned retrieval process and supporting technologies to maximise the use of research content while maintaining attribution to the original authoritative source.
ResearchGenie AI Chat is a chatbot designed for investment research that can be embedded as a web component or used in third-party chat frameworks such as Microsoft Teams.
ResearchGenie AI Chat harnesses the power of Fusion Search for AI to ensure answers are based on the most relevant, authoritative, and recent research publications from your corpus.
At Limeglass, we specialise in investment research discovery technology. We understand the importance of providing high-quality, relevant, and up-to-date answers, along with seamless access to the original authoritative source content.
ResearchGenie AI Chat is a powerful tool allowing your clients and sales team to unlock the breadth of your research coverage, resulting in strong ‘Trusted Advisor’ relationships.
If you would like to speak with the team or book a demo to see how our technology can empower your team, please get in touch using the form below: