Dynamic Knowledge Graph Application

A Visual Approach to Data Exploration

Leverage the power of natural language queries to populate Axon’s knowledge graphs with answers from structured and unstructured data sources stored in a Layar Data Fabric. Axon harnesses powerful BERT-modeled deep learning text analytics to derive greater value and insights from the Layar Reference Biomedical Data Fabric as well as internal document repositories, data storages, and real-time data streams. Drill down deeper by overlaying filters for named-entities, ontologies, or common answers across multiple questions asked in the knowledge graph.

Learn more about how Axon can fundamentally change the way you explore data assets within your organization.

Dynamic Knowledge Graphs

Visualize Novel Data Relationships

The knowledge graph offers a streamlined way to visualize key terms and evidence related to each user inquiry. A user can ask multiple questions in the application and find connections across their data fabric, presenting an opportunity for novel relationship discovery.

Natural Language Question Answering

Ask Questions of Your Integrated Data Fabric

Axon enables users to ask questions and retrieve deep learning A.I. answers from integrated content in Layar Data Fabrics. Axon uses a dynamic approach to continuously update the graph with new information, and all answers are linked to their original evidence.

Named Entity Recognition (NER)

Identify & Categorize Data Fabric Concepts

Axon leverages NER to identify and categorize terms and phrases from content integrated in Layar Data Fabrics. Axon identifies a wide array of life science NER concepts (proteins, cells lines, diseases, etc.) as well as several business development concepts (organizations, people, locations). NER concepts are continuously updated and refined by our deep learning models to reflect the current language of the domain, and novel terms previously not mentioned in literature (such as COVID-19).

The National Institute for Health and Care Excellence (NICE)PubMed AbstractsPubMed Central (PMC) Open AccessClinicalTrialsUS Patent Office (USPTO)PubChem

Life Sciences Reference Data Fabric

Access to Pre-Built Sources

Connect to millions of life-science and legal texts for research and analytics, continuously analyzed by Layar using advanced deep learning text analytics algorithms. Retrieve answers from documents within PubMed, Clinical Trials, the US Patent and Trademark Office, and more.

Learn more about the Layar Reference Biomedical Data Fabric

Organize Knowledge Graph

Filter Graph Based on Node Data

Organize the nodes in your knowledge graph by filtering based on database, NER concepts, ontologies, dates, and more.

Filter Answers With Ontologies

A top down approach to ontologies, users can upload ontologies into the knowledge graph and apply them as a filter on top of the deep learning derived answers. This enables users to observe answers that are consistent between a known ontology and the novel answers coming from the system. The application already provides Gene Ontology (GO), SNOMED Clinical Terms (SNOMED CT), and the Human Protein Ontology (HPO) out-of-box.

Diverse Export Options

Connect to Third-Party Applications

Export all metadata, literature, and answers from Axon into an HTML, GraphML, or CSV for further downstream analysis. These options offer users an easy solution to connecting their Axon knowledge graphs into third-party applications.

Import Data from External Graph Databases

Pull structured data from a third party vendor application into Axon. If a question yields an answer that is also present in the graph database, any properties listed for that entity are displayed directly in Axon.


View Supporting Evidence for Answers Derived from Vyasa Question Answering

Drill down into the scientific articles that Axon uses as supporting evidence for each answer-node it generated in the knowledge graph. Axon’s deep learning A.I. agents collect information from files across your data fabrics to return the these supporting documents for you to quickly the assess the relevance of the evidence for a given node.

Use Cases

Rare Disease Research

Rare diseases are those that affect less than 200,000 people and, as can be expected, studying these elusive diseases can be difficult. Synapse allows efficient and deep exploration of massive amounts of text data that might otherwise remain hidden.

Legal Research

Manual research is time consuming and modern search tools are limited in scope. Synapse utilizes its understanding of semantics to drive efficient discovery and allows the focus to return to the current case.


Dynamic Knowledge Graph Application

Axon enables derivation of dynamically generated knowledge graphs directly from integrated data and documents sources integrated in a Layar Data Fabric.

Find more support in our help center about:

  • The Basics of Axon
  • Narrowing Down Results with Filters
  • Understanding Evidence View & Supporting Documents