Featured Publications
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In The News
Computing on massive amounts of data takes time, energy and resources. To get the most out of the knowledge graphs, high performance computing is necessary, and scaling is a requirement for high performance computing.
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Data Sheets
Financial Services Industry Overview: Financial Services
Katana Graph helps financial services companies more effectively detect fraud in real time, while also seizing new business opportunities through expanded, personalized services.
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In The News
In the twelve months since its launch the company has raised $28.5 million in a round led by Intel Capital and secured clients in the pharmaceutical, financial services, security and electronic design automation sectors.
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Data Sheets
Financial Services Fraud Detection
Katana Graph has developed a next generation graph intelligence platform that provides breakthrough processing essential for today’s real-time anti-fraud applications. Katana Graph efficiently handles highly complex graph queries, algorithms and deep learning models, at massive scale and speed that other graph solutions simply cannot match.
Recent Blog Posts
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Blog
Optimizing Large-Scale Distributed Graph Neural Networks on Intel CPUs
Training Graph Neural Networks on Large Graphs Graph neural networks (GNNs) are a powerful tool for applying machine learning techniques to graph data. They allow us to generate or transform features on vertices and edges using deep neural networks to make them useful for a wide range of applications including fraud detection, product recommendation, and drug discovery.
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Blog
Rethinking Buyer Behavior Algorithms
To standard traffic analyzers, one click is as good as another. Our impulse purchases and our most prized procurements are all weighted equally by the algorithms through which vendors characterize us as consumers. We still see advertisements for now-shelved quarantine hobbies as we scroll through our daily news because click-counting and similar metrics have failed to reliably predict our actual interest levels.
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Blog
Graph Neural Networks for Credit Modeling
The financial services sector has many early adopters of sophisticated analytics techniques involving graph computing. Graph AI is regularly used in this industry for applications such as fraud detection, anti-money laundering, and other criminal activities.
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Blog
Katana Graph’s Analytics Python Library
As businesses grow and face increasing data challenges, they must find ways to tackle more expansive problems in shorter time windows. The most essential tools a company has at its disposal for addressing real-world data problems are modern algorithms. Businesses that take an algorithmic approach can tackle bigger problems with larger numbers of variables and can make better decisions than those that don't. Data is unquestionably the world’s most valuable resource today.
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Blog
K-Core and K-Truss Algorithms
K-core and k-truss algorithms assist with community search in large graphs and are used to identify cohesive portions of a graph based on specific metrics, particularly in mining applications. Discovering dense subgraphs is an essential task in graph mining, and is valuable in the analysis of social networks, biology, and identifying crime rings. Both algorithms proceed by iteratively removing components that do not meet a specified metric to produce a subgraph. By removing extraneous components, a user of the algorithm can produce simplified versions of large, complex graphs to provide clarity and understandability. Cohesive subgraphs allow the user to identify significant connections within their graph without a great deal of computational requirements.
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Blog
Clustering Coefficient Functions
The clustering coefficient algorithm is typically used on homogeneous, undirected graphs to determine which nodes cluster together and the likelihood that a node’s neighbors are also connected. For example, if a person’s friends are also friends with each other, the node representing that person has a high clustering coefficient. A low clustering coefficient, on the other hand, indicates a graph is composed of several weak ties. A clustering coefficient might be viewed roughly as the ratio of common friends in a social network compared to all possible connections a person might have.
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Blog
Community Detection Using Label Propagation Algorithm
Many networks — of people, bacteria, or computers — have a community-like structure. Quickly finding communities within large networks is a common task of the label propagation algorithm (LPA), a semi-supervised machine learning algorithm that assigns labels to the vertices of a graph that represents such a network.
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Blog
Louvain Community Detection
Louvain clustering is an algorithm for community detection that serves as an unsupervised, agglomerative, bottom-up clustering method for undirected graphs.
Webinars & Podcasts
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Podcast
Interview: Keshav Pingali, Co-founder and CEO of Katana Graph
In this episode, Julian Torres of Behind Company Lines interviews Keshav Pingali, Co-founder and CEO of Katana Graph, about how we solve clients’ problems in various industries and the challenges that leaders face when running a technology company like Katana Graph.
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Podcast
The Benefits of Graph Databases
In this episode of Embracing Digital Transformation, Hadi Ahmadi, Director of Solutions Architecture at Katana Graph, discusses the benefits of graph databases with Darren Pulsipher, Chief Solutions Architect at Intel.
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Podcast
Diversity and Inclusion: A Database for All Seasons!
Years ago, there were precious few choices for database technology. Today there are hundreds of database technologies to choose from, each of them designed for a particular purpose. What’s the latest? Check out this episode of DM Radio to find out!
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Podcast
A Graph Is Worth a Thousand Words
In this episode of TWiT our CEO, Keshav Pingali, discusses how Katana Graph came to be and its ability to ingest data from a variety of disparate data sources to derive insights for the financial, health and life sciences, and cybersecurity industries.
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Podcast
CEO Discusses the Impact of AI-powered Graph Technology on our Lives
In this episode of the AI in Action podcast Keshav Pingali, CEO and co-founder of Katana Graph, discusses AI-powered graph technology and various use cases within Healthcare and Fintech.
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Podcast
CEO Extracts Actionable Insights from Massive Datasets
Keshav Pingali, CEO and co-founder of Katana Graph, joins the I AM CEO podcast to discuss Katana Graph’s origins and the duties and responsibilities of a CEO.
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On-Demand Webinar
On-demand Webinar: Building a Foundation for Scalable ML and AI
Artificial intelligence is making its mark on every aspect of computing and graphs are playing a key role in AI and big data analytics, providing insights in many domains through traditional graph algorithms and graph neural networks.
Latest News & Events
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Press Releases
Katana Graph announced that it will further its partnership with Intel, accelerating the way that data scientists can rapidly extract deep insights from large, connected datasets.
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Events
Katana Graph announced that Justin Fine, Director of Field Engineering at Katana Graph, will be presenting at the Data Science Salon 2022 in New York City on December 7.
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Events
Join Katana Graph at BioTechX this November 8-10, 2022, at the Basel Congress Center, Basel, Switzerland. We'll be at booth 28 demonstrating how our groundbreaking all-in-one platform puts unprecedented flexibility and scalability at your fingertips.
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Events
Meet the Katana Graph team on October 10-12, 2022 at the Westin Copley Place in Boston, MA, along with over 300 data and analytics leaders.
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Events
Katana Graph will be at the AI & Big Data Expo on Oct. 5 - 6 in Santa Clara, CA, demonstrating how our groundbreaking all-in-one platform brings your data into brilliant focus faster than ever before.
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Events
Join Katana Graph Sept. 27 - 28 in San Jose, CA, at Intel Innovation 2022 to explore the latest break-throughs in tech-accelerating computing.
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Events
Greg Steck, Senior Director of Industry Solutions at Katana Graph, will be presenting at the Gartner Data & Analytics Summit 2022 in Orlando, Florida from August 22nd to 24th.
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Events
Join us August 16th for this special roundtable webinar to learn about new ML technologies and strategies.
Data Sheets
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Data Sheets
Financial Services Credit Modeling
Achieving new breakthrough levels of improved lending outcomes requires continuous improvement of credit modeling using the most advanced predictive technologies possible, particularly graph AI.
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Data Sheets
Financial Services 360 Degree Customer Insights
Organizations have more customer data sources than ever—purchase history, campaign activity, interactions across all channels, demographics and countless more—which together can reveal new, 360-degree customer insights, including predicting future needs and wants.
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Data Sheets
Health & Life Sciences RDKit Integration
The success of your drug discovery innovation efforts depends heavily on the speed and accuracy in which hypotheses can be generated and tested. The Katana Graph intelligence platform fulfills this essential need for life sciences companies in ways alternative solutions simply cannot match.
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Data Sheets
The 2020 global pandemic forced organizations to accommodate a sudden, massive spike in remote work, business and communications. Many companies have found their identity and access management (IAM) systems cannot keep up with today’s highly complex and demanding identity landscape.
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Data Sheets
Technology Overview The Katana Graph Intelligence Platform
Katana Graph provides a Graph Intelligence Platform offering elastic performance at massive scale for Graph Queries (contextual search), Graph Analytics (path finding, centrality and community detection), Graph Mining (pattern discovery), and Graph AI (prediction).
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Data Sheets
Security System Intrusion Detection
Katana Graph Intelligence Platform detects a broad spectrum of intrusions in real time that might otherwise evade traditional IDS tools, through the power of next-generation graph analytics, mining and AI.
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Data Sheets
Health & Life Sciences Industry Overview: Life Sciences
Katana Graph offers a breakthrough graph intelligence platform that enables life sciences organizations to reap the huge potential of graph processing and AI, at levels of scale and performance no other data platform can match.
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Data Sheets
Health & Life Sciences Drug Discovery
Katana Graph enables life sciences knowledge workers to store, query, mine and develop AI models using heterogeneous data sources, to reveal breakthrough insights at levels of scale and performance no other data platform can match.
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Data Sheets
Financial Services Fraud Detection
Katana Graph has developed a next generation graph intelligence platform that provides breakthrough processing essential for today’s real-time anti-fraud applications. Katana Graph efficiently handles highly complex graph queries, algorithms and deep learning models, at massive scale and speed that other graph solutions simply cannot match.
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Data Sheets
Security Industry Overview: Security
Organizations are actively improving customer engagement and optimizing business operations. New technologies to fulfill these demands have been introduced, from the Internet of Things (IoT) to SaaS solutions capable of managing the most complex networks of customers, partners and distributors. However, these technologies have also become targets for cybercrime.
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Data Sheets
Financial Services Industry Overview: Financial Services
Katana Graph helps financial services companies more effectively detect fraud in real time, while also seizing new business opportunities through expanded, personalized services.