Latent Knowledge develops AI and natural language processing tools that enhance data analysis and knowledge extraction from unstructured data. Their technology enables researchers to efficiently process large datasets, improving the accuracy and speed of insights derived from complex information sources.
Funding
$20K raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Researchers often struggle to efficiently extract relevant insights from the overwhelming volume of unstructured data in academic literature and other complex information sources. Existing search tools often fail to surface critical connections between disparate documents, hindering interdisciplinary research and slowing down the pace of discovery.
Solution
Latent Knowledge offers LitView, a B2B SaaS platform that leverages AI and natural language processing to enhance data analysis and knowledge extraction. LitView transforms search results into visually clustered, semantically relevant texts, revealing significant relationships between articles and documents that traditional search methods miss. The platform enables users to iteratively refine searches with contextual information, apply technical translations, and replicate successful search models on new datasets. By providing a more intuitive and comprehensive search experience, LitView helps research teams cut through noisy data, accelerate the identification of key findings, and foster collaboration.
Target Audience
The primary target audience includes research teams in academia, law enforcement, and biomedicine, as well as R&D teams in various industries.
Features
- Semantic search across common research literature databases using natural language processing
- Visualization of search results as clusters of related texts, highlighting connections between documents
- Ability to save and replicate previous searches and search models
- Document upload feature to integrate proprietary data into the cluster space
- Support for interdisciplinary research searches across multiple fields
- Technical translation capabilities for cross-lingual information retrieval
- Workplace collaboration features for R&D teams