A couple of days ago, we hosted a Logistics Optimisation webinar. We covered some challenges of Logistics Chains and talked about how graphs, graph technology, and Hume can help you tackle them.
Everyone has a favourite grocery shop they usually go to, maybe the shop close to home, the one with the most competitive prices, the freshest fruit, or simply the best cake. Similarly, everyone may be inclined to buy from one particular e-commerce platform rather than another.
Last week we at GraphAware hosted yet another webinar. This time we talked about Money Laundering and how Hume can help you detect money laundering activities. Don’t worry if you missed it; here is your summary of what we covered.
Only a few things are more satisfying for a graph data scientist than playing with Neo4j Graph Data Science library algorithms, most probably running them in production and at scale. Possibly also using them to fight against scammers and fraudsters that every day threatens your business.
It is always a valuable opportunity to understand our product better and recognize user needs. At GraphAware, building Hume, a graph-powered insight engine, we are proud of making an impact on our customers’ success. However, we use Hume also to support our processes and help our own needs. In the case of the event that took place throughout December, we were also able to have great fun and integrate the team.
Last week, I had the pleasure of hosting a webinar with our Director of Product, Esther Bergmark, and our CTO, Christophe Willemsen. This webinar introduced our new release Hume 2.11, so we covered the most exciting features of the release, including no-code graph navigation, custom visibility of Actions in Perspectives, and Perspective API. The 2.11 version comes with more updates and advancements such as Configuration as Code and Polygons in Geospatial Analysis - about which you can read in our release blog.
We are proud to announce the 2.11 release of Hume. Advanced Expand is introduced to Hume with this release, which lets users create complex queries to navigate the graph without using Cypher. Additionally, the visibility of Actions can now be defined per Perspectives, enabling a tailored exploration experience; a GraphQL API exposes data from Perspectives so that other apps can leverage the power of Hume. And finally, Configuration-as-Code allows administrators to manage Hume configuration files in a repository.
About a year ago, I first logged into Hume - in the morning, I had started my new job at GraphAware, and a few hours later, I had a canvas in front of me with a few person nodes connected by relationships. Hume Visualisation. The graph: a murder mystery. Me: a newbie, never typed a line of code in any query language.
Just a couple of days ago, we hosted a Fraud Detection webinar. We chose to focus on credit card fraud to illustrate how Hume can help detect fraud faster. Our Director of Product, Esther Bergmark walked you through an example of a credit card company investigator looking into suspicious, fraudulent developments. Let me share what we covered at the webinar.
We are proud to announce the 2.10 release of Hume. With this release, Comments are introduced to Hume, which lets you add text, images, and links as comments to nodes and relationships. Additionally, Snapshots can now be shared, and Temporary Visualisations can be created and accessed by other users via a URL.
Welcome to the first blog in the business series of GraphAware blog! This series is designed for us non-techies out there. Personally, I was shocked when I found out how big and common knowledge graphs are and how often graph databases are used in today’s world - and I had first heard of them just a couple of months ago. So, for people like me, for marketers and non-tech people in business, I’ll try to open the door to the world of graphs, and their potential and take you through it step-by-step. It seems only appropriate that we start with...
This blog post is the first part in a series on Effective Graph Visualisations, showcasing features emerging from years of experience in the field.
Knowledge Graphs (KGs) have become one of the most powerful tools for modeling the relations between entities in various fields, from biotech to e-commerce, from intelligence and law enforcement to fintech. Starting from the first version proposed by Google in 2012, the capabilities of modern KGs have been employed across diverse applications, including search engines, chatbots, and recommendation systems.
Organisations do not suffer from a lack of data or qualified people who analyse it and draw conclusions but rather from the size of relevant data sets and the limited amount of time skilled people can spend on exploration and analysis. In this blog post we show how Hume Alerts can be used to solve this issue.
Not so long ago, our very own Luanne gave an amazing talk titled Maltaware: Discovering what to drink with Neo4j on Nodes2020. Luanne demonstrated the value of graphs, and why they are the perfect fit for recommendation engines with an example of a whisky recommendation engine. Let me quickly walk you through a summary of why graphs and recommendation engines go together so well.
GraphAware is now going through an extremely exciting phase. In 2020, we launched our own amazing product Hume, the only graph-powered insights engine in the world, which helps companies shed light on their complex data and make smart decisions. Since then, we have been rapidly growing in all aspects. Our ambitious plans will need plenty of talented people, who want to have a direct impact on a company’s success. Right now, we are already advertising for multiple vacancies, and the number will only grow in the coming months (check out our career page if you are already intrigued).
Before I started at GraphAware I spent many years in research, both academia and industry, focusing my attention on machine learning and image processing.
GraphAware is proud to announce the 2.9 release of Hume. With this release, Alerts are available in Hume, a feature that greatly simplifies the daily work of analysts, data scientists, investigators, and data-savvy business users. And there is more:
When we started our journey with Neo4j over ten years ago, we were just a bunch of passionate techies trying to convince the world about the power of graphs. We were blogging, running meetups, writing open-source code, speaking at conferences, trying to preach graphs to a like-minded crowd.
Say you have a graph-based project in mind. Be it research in life sciences, a fraud detection machine, or possibly a recommendation app. Anything that relies heavily on relationships between data points is a good case for a graph.
It has been over 8 years since I’ve written the first lines of code for the GraphAware Neo4j Framework as part of my MSc. thesis. That’s when the name GraphAware, as well as the (then) one-man show Neo4j consulting company was born. It is therefore my bittersweet duty to take you on a small trip down the memory laneand announce that we have decided to discontinue the development and support of the Framework and all of its modules.
GraphAware is proud to announce the 2.8 release of Hume, our graph-powered insights engine. The release adds further unique capabilities to Hume’s knowledge graph visualisation and graph data analysis capabilities. Analysts, data scientists, investigators, and data-savvy business users will profit from these benefits:
CDC (Change Data Capture) is a well defined software design pattern for a system that monitors and captures data changes so that other software can respond to those events.
GraphAware is proud to announce the 2.7 release of Hume, our graph-powered insights engine. The release significantly enhances Hume’s knowledge graph visualisation and graph data analysis capabilities. Analysts, data scientists, investigators, and data-savvy business users immediately get the following main benefits:
Enterprise Integration has existed since many, many years. Although it might seem like an old set of patterns, the reality is that more and more data silos, protocols and systems have been created in recent times which increase the need for the capabilities of an Enterprise Integration platform.
In our last MET Art Collections post we ingested and processed part of a dataset containing more than 470,000 artworks from The Metropolitan Museum of Art and created a knowledge graph using Hume, GraphAware’s insights engine.
The Metropolitan Museum of Art recently published a dataset of more than 470,000 works of art under the CC-zero License. Representing such a collection as a knowledge graph allows us to explore it in a unique way - seeing the artworks, their authors, donors, mediums, tags, or art movements deeply connected, being able to traverse the links between them and discover unexpected relations.
In an increasingly complex and hyperconnected world, organizations need a level of insight, collaboration and optimization into their data that is locked away within different systems and siloed within the different teams. Information is hidden and opportunities are missed because of the lack of a single system to host, analyze, and visualize their data.
Graphs are a perfect fit for IT Operations. Right from dependency management to impact analysis and capacity to outage planning, the interconnectedness of the components that make up networks and services, modelled naturally as a graph enable various teams such as support, help desk and devops to navigate potentially complex relationships.
GraphAware is proud to announce the release of Hume 2.6. This new release brings some major updates and exciting new features to our customers. In particular:
If you have read our post Hume in Space: Monitoring Satellite Technology Markets with a ML-powered Knowledge Graph, you surely wonder: is there a way to extract relations among named entities without heavy investment? Investment in terms of time to label training dataset and to develop, train and deploy a machine learning model?
Everyone has a passion for something. Be it music, politics, sports, coffee or … pancakes. Such passion makes you strive for new information, for understanding of the current trends. Take pancakes: you might watch for new recipes on your favourite website, you might look at cooking shows or youtube videos to get more inspiration about how to serve them … but overall, you can probably handle this pretty well. It’s not like there is much room for revolutionising the pancake recipe.
GraphAware Hume helps governments in keeping their countries safe. In this 15-minute video, we demonstrate the use of Hume for contact tracing and smart quarantine in the context of the current coronavirus pandemic. Specifically, we will see how Hume can identify people at risk using actual and potential contact tracing, suggest who should be informed or quarantined, visually explain why someone is at risk, find quarantine offenders, and much more.
BOSTON, July 23, 2019 /PRNewswire/ – GraphAware, a leading Neo4j ISV and consulting practice, today announced the official launch of its Italian Research and Development entity Graph Aware S.r.l., headquartered in Lecce, Italy.This strategic investment by GraphAware represents a significant expansion as an ISV, with a fast growing development team of thought-leaders in GraphDBs with Neo4j, Natural Language Processing (NLP), Machine Learning (ML) and Artificial Intelligence (AI).Led by Chief Scientist Alessandro Negro and CTO Christophe Willemsen,the Lecce R&D center is the main lab and development center for GraphAware’s flagship software platform Hume- with a dedicated local and remote development team...