Are you interested in finding out how open data might provide you with a detailed map of a business environment? Risk Hunter is a unique visualized graph platform for researching and investigating UK companies using connected data, powered by Graphlytic. See how it works.
Powerful HTML5 based graph visualizations with cytoscape.js library works with every major browser and platform
Graphlytic is powered with the world's leading graph database Neo4J which enables us to give you fantastic performance
Look for patterns in your data with easy-to-use layouts, filtering or mapping data to visual properties like color or size
With Jobs it's easy to write and schedule your own scripts for importing data, searching patterns (with Cypher) and sending emails
Data analysis doesn't have to be a lonely job. Collaborate with other users and share your findings or export images and data
Contact us if you are interested in using Graphlytic in specific business cases. We are happy to help you with setup
With Graphlytic, we enabled our customer to work with the configuration database data more efficiently and easier, resulting in faster, smarter decisions and in the involvement of other organizational units to regular use of this data in decision making.
ITIL Expert at MIM, s.r.o.
Connections and relationships hold the key to truth. Our analytical engine, R!sk Hunter, performs the graph queries in the unique graph database of the entire UK corporate universe for investigations, due diligence, forensics. Graphlytic visualization is a perfect user interface for searching and exploring the network among millions of relationships. It helps us to spin-up the engagement with our potential customers.
CEO at Regulation Technologies Ltd.
We have used Graphlytic for multiple cases and found it very useful for gaining a deeper understanding before doing business decisions or investment. Our IT department utilized the tool to analyze code structure in the next generation of our core system to optimize it. We, at the business branch of the company, applied Graphlytic graph visualization to get a better knowledge of the unique communication patterns in our company that led to increased efficiency of our sales processes.
Sales & Marketing Director at Commander Services, s.r.o.
The first step is to import your data into the graph database. Any method of importing data into Neo4j can be used and Graphlytic's Jobs is one of such methods. Jobs can be run on-demand or scheduled to run automatically e.g.every night. With Jobs, you can keep your graph data up to date, send email notifications when something goes wrong or when a job finds predefined patterns (with Cypher) in data.
Search with fulltext in all data or in predefined collections of your graph data and find starting points for the graph visualization. It's easy to look for and to visualize graph patterns with the Cypher query language. Graphlytic provides an advanced graph search interface that can be used by non-technical users as well as by professionals.
Graph visualization is a powerful way to find patterns which can't be seen from a table or a chart. Different layouts reveal different patterns in graph visualization. Data to style mappings are used to enhance visual signal with properties like color, size, or shape of nodes and relationships. Filter out outliers; look for timeline dependencies; and get meaningful information as clear as possible.
Graph visualizations can be saved and reloaded later with automatic notification on any changes in the graph data. Visualizations can be exported as images or CSV files for use in different applications. Graph visualizations can be also shared with other users in the application to provide effective collaboration on bigger projects.
This is the simplest way to use Graphlytic. You can install Neo4J and Graphlytic on the same computer and start analyzing graphs right away. Check out our LITE version when you are a single analyst.
When you need multiple users to work with the same data, you can install Graphlytic on a server or in a cloud; then create users, assign them to groups and control which user can access which part of the data. You now have everything under control.