Aj Matias's Linkedin Analytics

Fathom offers a simple path for creating a flexible data pipeline that everyone in the company can use for queries. Using optical character recognition enhanced with AI trained for biopharma, we are able to digitize and normalize content that has historically been inaccessible because of its location or format. Our ability to convert data and maintain the underlying associations is what powers our very flexible querying tools. Once the data is extracted, we contextualize it using several techniques including analyzing the document structure, understanding the meaning and relationships encoded within the language itself, and interpreting scientific-specific information such as units and equations. At this point the data is ready for search-based queries across any subset of the available data sources. Our search approach allows for great flexibility as source data changes or is added, and is conversationally-based so users don’t need to learn traditional database query languages to access the system. The search queries output tabled results that can be easily analyzed and downloaded.