US EVENTS
April 13th -14th, 2022
Discuss the vast threat landscape facing the nation and the local community alike.
April 20th, 2022
Apex Private Roadshow Dinner Series are customized turnkey engagements that are tailored to meet your unique business needs.
April 28th, 2022
Our assembly gives executives and service providers the opportunity to engage with like-minded executives and industry leaders both physically and virtually.
June 21st, 2022
Apex Private Roadshow Dinner Series are customized turnkey engagements that are tailored to meet your unique business needs.
June 28th, 2022
CDO and Heads of Artificial Intelligence / Machine Learning have become the most dynamic amongst their peers.
Apex Seattle Private Dinner CIO & CTO Digital Transformation
July, 2022
Apex Private Roadshow Dinner Series are customized turnkey engagements that are tailored to meet your unique business needs.
August 16th-18th, 2022
Ai4 2022 brings together business leaders and data practitioners to facilitate the adoption of artificial intelligence and machine learning technology.
August 22nd-24th, 2022
Unleash Innovation. Transform Uncertainty.
October 10th-12th, 2022
Our award winners are the innovative thinkers and problem solvers of the world, and we are honored to be able to recognize them!
Evanta CDO Executive Summit - Chicago
November, 2022
Get together with Chicago’s top CDOs to tackle shared business challenges and critical priorities facing your role today.
EMEA EVENTS
March 31st, 2022
Keep up to date with the latest knowledge and thought leadership on fraud prevention, detection, and investigations.
April 14th-16th, 2022
Attend our session on Blockchain Analysis with Graph Neural Networks.
May 18th & 19th, 2022
Heiter bis wolkig. Clouds & Co. für Transparenz und Resilienz.
US EVENTS
Decision Trees in TigerGraph
This blog post was originally featured on Towards Data Science and is written by Parker Erickson, Data Science / Machine Learning Intern at TigerGraph Make
MinHash Based Fuzzy Match on Graph
Many graph use cases require fuzzy matching, a method used to find similar, but not exactly matching, phrases in a database. Some examples of fuzzy
Trillion edges benchmark: new world record beyond 100TB by TigerGraph featuring AMD based Amazon EC2 instances
Graph databases have become increasingly popular in recent years, as they are uniquely suited to handle complex, interconnected data. As data sets continue to grow,
TigerGraph Puts State-of-the-Art Graph Neural Networks within Reach
In a relatively short time, machine learning has completely transformed almost every facet of technology in the business world and in our day-to-day lives. From
Embracing a New Chapter: A Message From the New CEO
In a relatively short time, machine learning has completely transformed almost every facet of technology in the business world and in our day-to-day lives. From
How Is Graph Database Used to Combat Money Laundering? ~ by Mingxi Wu, CEO, TigerGraph
Figure 1: AML generic workflow. Financial accounts are linked to many transactions. Alert entities are suspicious accounts that are presented to fraud analysts, who can
Understanding Bank Fraud ~ by Harry Powell
Bank fraud is a serious concern that affects financial institutions and their customers worldwide. Large organized criminal groups are often the primary perpetrators of fraud,
Harnessing the Potential of Graph AI: Insights from a Marketer’s Perspective
In the ever-evolving landscape of technology, certain innovations emerge that have the potential to shape the future. One such innovation is the emergence of graph
Graphs for Good: Transforming Refugee Support with UAWelcome’s Revolutionary Project
In a world where technology continually evolves, one innovative project stands out as a beacon of hope—UAWelcome. Harnessing the power of graphs for good, UAWelcome
Supercharging Fraud Detection: How a Leading Financial Institution Utilizes TigerGraph for Real-Time Entity Resolution
In today’s fast-paced financial landscape, real-time fraud detection has become essential for safeguarding customer assets and preserving trust in financial institutions. One leading investment bank
How Two Forbes Top 20 Businesses Transformed Their Core Rules Engines
In today’s rapidly evolving business landscape, agility and efficiency are crucial for staying competitive. To achieve this, businesses rely on rules engines to automate decision-making
It’s Time to Harness the Power of Graph Technology [Infographic]
It’s time for your enterprise to harness the power of graph technology. A graph database platform – like TigerGraph – stores your data in intuitive,
Graph-Powered Analytics: Why You Need It and How to Learn It
Businesses need to stay ahead of the competition, to cut losses, and to find more revenue. By looking at their data as a network and
Integrating TigerGraph and Large Language Models for Generative AI
by Parker Erickson Introduction to Large Language Models Generative AI and Large Language Models are on everyone’s mind – they have been proven to be
Using Graph Machine Learning to Improve Fraud Detection Rates
by Parker Erickson Fraud comes in all shapes and forms across many industries; from account takeovers, to transaction fraud, the financial services industry to healthcare,
Reduce AML Investigation Costs with TigerGraph
by Parker Erickson and Victor Lee Anti-Money Laundering (AML) refers to the set of laws, regulations, and procedures aimed at preventing and detecting money laundering
Advancing Entity Resolution for Fraud Detection with TigerGraph
First in our series of blogs straight from our engineers to you. In today’s digitally interconnected world the proliferation of data has presented both unprecedented
Utilizing Multi-edge for Temporal Search in a Sales Agent Hierarchy
Introduction Hello everyone! I’m Xuanlei Lin. I have worked as a solution engineer at TigerGraph for two years and as a customer success consultant for
Graph-Powered Cybersecurity
If you’re reading this, then your daily personal and work life is probably dependent on information that is stored and accessed digitally. People and processes
November 2023 TigerGraph Cloud Update
Welcome to the November 2023 update for TigerGraph Cloud, the cutting-edge platform that revolutionizes the way you manage and analyze your graph data. In this
Optimized Counting of Common Neighbors/Vertices in GSQL
By Prateek Agrawal Graph analytics plays a crucial role in finding hidden relationships within large datasets. One fundamental operation in this domain is calculating the
Graph Databases 101: Your Top 5 Questions with Non-Technical Answers
The world has always been built around connections, but the world today is more hyper-connected than ever before. Tapping into the power of these rich,
The Connected Customer: Building the Foundation with TigerGraph
In the rapidly evolving world of customer-facing businesses, providing an exceptional omnichannel customer experience has become the key to success. As online retail sales have
The Jellyfish and the Flatworm: a Story About AI Strategy
Many executives are pondering difficult decisions about making large investments in AI. For many of them, their lack of a technical background makes it difficult
5 Reasons Why You Can’t Miss Graph +AI Summit 2024
As the Head of Marketing at TigerGraph, I’m thrilled to extend a warm invitation to all enthusiasts, professionals, and curious minds to join us at
TigerGraph CoPilot Enters Public Alpha Release
We are thrilled to announce the public alpha release of TigerGraph CoPilot, the AI assistant for TigerGraph-powered solutions. It is now available at https://github.com/tigergraph/CoPilot for
Enhanced Data Analytics: Integrating NVIDIA Rapids cuGraph with TigerGraph
In the rapidly evolving landscape of data analytics and artificial intelligence (AI), the recent talk by Dan McCreary, Head of AI at TigerGraph, at the
Understanding Graph Embeddings
A sample of customer data in a knowledge graph and the embedding vector attached to the graph. by Dan McCreary, Head of AI at TigerGraph
Creating LLM-Friendly Definitions for TigerGraph CoPilot
A sample of customer data in a knowledge graph and the embedding vector attached to the graph. by Dan McCreary, Head of AI at TigerGraph
The Rise of GQL: A New ISO Standard in Graph Query Language
by Mingxi Wu We’re thrilled to celebrate a significant milestone in the world of database technology: the publication of the first version of the ISO
Putting the Customer First: The Power of the Empty Chair
When companies innovate, one key principle stands tall: the customer should be at the center stage. At TigerGraph, we champion this principle through the concept
Supply Chain Digital Twins Enable Analytics and Resiliency
In March 2024, the Francis Scott Key Bridge across the entrance to Baltimore Harbor collapsed when a cargo ship lost power and crashed into it.
Graph Developer Proficiency Rating
Graph Developer Proficiency Rating A Simple Rating System for Staffing Graph Projects A business unit leader once asked me a simple question: When will
Graph Technology for Augmented Intelligence in AI Reasoning
In today’s data-driven world, artificial intelligence (AI) is transforming industries by providing unprecedented capabilities in automation, prediction, and decision-making. However, as we integrate AI systems
Creating a Graph Center of Excellence
Best practices for promoting positive change In today’s high-velocity change-driven business climate, organizations are increasingly turning to specialized teams known as Graph Centers of Excellence
Uncovering Financial Fraud: How Graph Technology Transforms Detection in Banking
It’s no secret that banks are constantly battling a formidable adversary: fraud. And unfortunately, financial institutions continually face staggering losses despite investing billions in sophisticated
Welcoming Rajeev Shrivastava as CEO: A New Era of Innovation at TigerGraph
Today, we welcome Rajeev Shrivastava as our new CEO at TigerGraph! Rajeev is a highly accomplished technology executive with a wealth of experience in the
TigerGraph Welcomes Two Exceptional Leaders to Drive Customer and Marketing Excellence
We are thrilled to announce the appointment of two outstanding executives to TigerGraph’s leadership team. Mike Crane joins us as Chief Customer Officer, and Paige
Introducing TigerGraph Savanna: Our Next-Generation Cloud Native Graph Database for Supercharging AI Systems
Introducing TigerGraph Savanna: Our Next-Generation Cloud Native Graph Database for Supercharging AI Systems In an era where data is increasingly interconnected, the need for powerful
TigerGraph Hybrid Search: Graph and Vector for Smarter AI Applications
TigerGraph Hybrid Search: Graph and Vector for Smarter AI Applications AI Search is Broken. Let’s Fix It. AI-powered search is evolving beyond traditional methods. You’ve
TigerGraph DB Community Edition – The Most Powerful Free Graph + Vector Database for Turbocharging AI
Unlocking the Power of Graph AI for Developers, Researchers, and Startups Graph databases have come a long way from powering social networks and recommendation systems
Unleashing AI’s Potential: Why Graph Databases are the Secret Weapon
Unleashing AI’s Potential: Why Graph Databases are the Secret Weapon Artificial intelligence is rapidly transforming industries, but its biggest challenge remains: understanding relationships within data
Google’s $32B Cybersecurity Bet on Wiz Validates the Power of Graph & Signals a Paradigm Shift
Google’s $32B Cybersecurity Bet on Wiz Validates the Power of Graph & Signals a Paradigm Shift Google’s recent agreement to acquire cloud security firm Wiz
Demystifying Black Box AI with Graph Technology
Demystifying Black Box AI with Graph Technology Artificial intelligence is reshaping how decisions are made—driving automation, accelerating insights, and enabling autonomy at scale. But with
Why Financial Services Is Ground Zero for Agentic AI + Graph
Why Financial Services Is Ground Zero for Agentic AI + Graph Financial services is fundamentally an industry of relationships. Every transaction, account, merchant, regulator, and
Graph Technology Mitigates Tariff Fallout by Modeling Supply Chain Disruptions
Graph Technology Mitigates Tariff Fallout by Modeling Supply Chain Disruptions Policy shifts, trade tensions, and a continuously evolving geopolitical landscape—for global supply chain leaders, change
Fraud Moves Fast – Your Detection System Needs to Be Smarter and More Agile
Fraud Moves Fast – Your Detection System Needs to Be Smarter and More Agile Fraud is no longer a matter of isolated bad actors or
Why Agentic AI Needs More Than Just Rules (It Needs Guardrails)
Why Agentic AI Needs More Than Just Rules (It Needs Guardrails) Traditional AI models often operate in rigid, rule-based environments, but real-world scenarios demand nuance.
The Agentic AI/Graph Database Combo Powering Emerging Applications
The Agentic AI/Graph Database Combo Powering Emerging Applications Static AI models that provide insights on demand are no longer enough. Today’s enterprise needs systems that
Why Fraud & Risk Teams Are Adopting Graph Analytics
Why Fraud & Risk Teams Are Adopting Graph Analytics Fraud isn’t just a data problem—it’s a relationship problem. This new reality is something industry leaders
Cybersecurity & Graph Analytics: Why Speed and Scale Matter in Threat Detection
Cybersecurity & Graph Analytics: Why Speed and Scale Matter in Threat Detection Modern cybersecurity threats don’t happen in isolation—they unfold as chains of behavior across
