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AiThority Interview with Dr. Jans Aasman

Jans Aasman, please tell us about your current role and the team / technology you handle at Franz.

As CEO of Franz Inc., I drive the overall technology vision for our Enterprise Knowledge Graph solutions and ensure our customer projects deliver the ROI results expected with graph based architectures.

Franz Inc. is composed of an expert team with skills in Graph Databases, Semantic technologies, Graph Visualization, AI, NLP and Machine Learning.  Our domain knowledge encompasses large enterprises in Healthcare, Pharma, Customer Support, and Intelligence Agencies.

Our main business today revolves around AllegroGraph, a Semantic Graph platform that allows infinite data integration through a patented approach unifying all data and siloed knowledge into an Entity-Event Knowledge Graph solution that can support massive big data analytics. AllegroGraph’s FedShard feature utilizes patented federated sharding capabilities that drive 360-degree insights and enable complex reasoning across a distributed Knowledge Graph. AllegroGraph is utilized by dozens of the top Fortune 500 companies worldwide.

We also offer a popular data visualization and no-code query builder called Gruff – the most advanced Knowledge Graph visualization application on the market, which we recently integrated into Franz AllegroGraph. Gruff enables users to create visual Knowledge Graphs that display data relationships in views that are driven by the user. Ad hoc and exploratory analysis can be performed by simply clicking on different graph nodes to answer questions. Gruff’s unique ‘Time Machine’ feature provides the capability to explore temporal context and connections within data. The visual query builder within Gruff empowers both novice and expert users to create simple to highly complex queries without writing any code.

Read the full interview at AIThority.




Comex AI Conference 2021 (Recording)

COMEX is the largest Technology, Communications, Innovation and Digital Transformation show in the Sultanate of Oman and offers exhibitors and visitors a comprehensive and highly specialized platform for industry leading discussions, knowledge-sharing, B2B meetings.

Dr. Sheng-Chuan Wu presented – Using AI for Practical Business Applications




The Future of AI: Machine Learning and Knowledge Graphs

Bringing knowledge graph and machine learning technology together can improve the accuracy of the outcomes and augment the potential of machine learning approaches. With knowledge graphs, AI language models are able to represent the relationships and accurate meaning of data instead of simply generating words based on patterns.

Read this special report to dive into key uses cases, best practices for getting started, and technology solutions every organization should know about.

The Future of AI: Machine Learning and Knowledge Graphs




Gartner Case Study: Entity-Event Knowledge Graph for Powering AI Solutions (Montefiore)

Gartner featured Franz’s customer, Montefiore Medical Center, in a research report on Montefiore’s Entity-Event Knowledge Graph:

“AI solutions are often hindered by fragmented data and siloed point solutions,” according to Gartner’s Chief Data and Analytics Officer Research Team. “Montefiore’s data and analytics leader used semantic knowledge graphs to power its AI solutions and achieved considerable cost savings as well as improvements in timeliness and the prediction accuracy of AI models.” Source: Gartner Case Study: Entity-Event Knowledge Graph for Powering AI Solutions (Montefiore) – Subscription required.




KMWorld 100 Companies that Matter Most – Franz Inc.

Franz Inc., is proud to announce that it has been named to The 100 Companies That Matter in Knowledge Management by KMWorld. The annual list reflects the urgency felt among many organizations to provide a timely flow of targeted information. Among the more prominent initiatives is the use of AI and cognitive computing, as well as related capabilities such as machine learning, natural language processing, and text analytics.

“Flexibility, agility, and the ability to pivot are attributes that have become critical to forward-thinking companies—and that is particularly the case now. Successful organizations don’t want to merely survive; they want to dominate their market sectors. But to do that, they need the right tools and products,” said Tom Hogan, Group Publisher at KMWorld. “Amidst the dramatic changes taking place today, innovative organizations are seeking new approaches to improve their processes. The 2021 KMWorld 100 is a list of leading-edge knowledge management companies that are helping their customers to expand access to information, leverage new opportunities, and accelerate growth.”

Read More about Franz Inc.




Gartner Hype Cycle for AI – Knowledge Graphs

According to Gartner’s 2020 Hype Cycle for Artificial Intelligence – Despite the global impact of COVID-19, 47% of artificial intelligence (AI) investments were unchanged since the start of the pandemic and 30% of organizations actually planned to increase such investments, according to a Gartner poll. Only 16% had temporarily suspended AI investments, and just 7% had decreased them.

“AI is starting to deliver on its potential and its benefits for businesses are becoming a reality”

Gartner’s – AI Hype Cycle Article 

The Hype Cycle growth is consistent with Franz’s customer interest in our Enterprise Knowledge Graph Solutions – Read our recent White Paper.

 

 




Franz Inc. Named an AI 50 Company by KMWorld

AllegroGraph Powering Intelligent Knowledge Graph Solutions

Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology for Knowledge Graph Solutions, today announced that it has been named to The AI 50 – Companies Empowering Intelligent Knowledge Management Companies by KMWorld.  The annual list reflects the urgency felt among many organizations to provide a timely flow of targeted information. Among the more prominent initiatives is the use of AI and cognitive computing, as well as related capabilities such as machine learning, natural language processing, and text analytics.   This list recognizes companies based on their presence, execution, vision and innovation in delivering products and services to the marketplace.

“As the drive for digital transformation becomes an imperative for companies seeking to compete and succeed in all industry sectors, intelligent tools and services are being leveraged to enable speed, insight, and accuracy,” said Tom Hogan, Group Publisher at KMWorld.  “To showcase organizations that are incorporating AI and an assortment of related technologies—including natural language processing, machine learning, and computer vision—into their offerings, KMWorld created the “AI 50: The Companies Empowering Intelligent Knowledge Management.”

“Franz Inc. has a rich history in AI and we are honored to receive this acknowledgement for our efforts in delivering AI Knowledge Graph Solutions,” said Dr. Jans Aasman, CEO, Franz Inc. “In the past year, we have seen demand for Intelligent Data Fabrics take off across industries along with recognition from top technology analyst firms that Knowledge Graphs provide the critical foundation for Enterprise Wide Data Fabrics.    Our recent launch of AllegroGraph 7 with FedShard, a breakthrough that allows infinite data integration to unify all data and siloed knowledge into an Entity-Event Knowledge Graph solution will catalyze Data Fabric deployments across the Enterprise.”

Gartner’s Top 10 Trends in Data and Analytics for 2020 noted “Relationships form the foundation of data and analytics value.  By 2023, graph technologies will facilitate rapid contextualization for decision making in 30% of organizations worldwide. Graph analytics is a set of analytic techniques that allows for the exploration of relationships between entities of interest such as organizations, people and transactions.  Data and analytics leaders need to evaluate opportunities to incorporate graph analytics into their analytics portfolios and applications to uncover hidden patterns and relationships. In addition, consider investigating how graph algorithms and technologies can improve your AI and ML initiatives.” (Source: Gartner, Top 10 Trends in Data and Analytics for 2020, June 9, 2020).

“Graph databases and knowledge graphs are now viewed as a must-have by enterprises serious about leveraging AI and predictive analytics within their organization,” said Dr. Aasman “We are working with organizations across a broad range of industries to deploy large-scale, high-performance Entity-Event Knowledge Graphs that serve as the foundation for AI-driven Data Fabrics for personalized medicine, predictive call centers, digital twins for IoT, predictive supply chain management and domain-specific Q&A applications – just to name a few.”

Forrester Shortlists AllegroGraph

AllegroGraph was shortlisted in the February 3, 2020 Forrester Now Tech: Graph Data Platforms, Q1 2020 report, which recommends that organizations “Use graph data platforms to accelerate connected-data initiatives.” Forrester states, “You can use graph data platforms to become significantly more productive, deliver accurate customer recommendations, and quickly make connections to related data.”

Bloor Research covers AllegroGraph with FedShard

Bloor Research Analyst, Daniel Howard noted “With the 7.0 release of AllegroGraph, arguably the most compelling new capability is its ability to create what Franz refers to as “Entity-Event Knowledge Graphs” (or EEKGs) via its patented FedShard technology.” Mr. Howard goes on to state “Franz clearly considers this a major release for AllegroGraph. Certainly, the introduction of an explicit entity-event graph is not something I’ve seen before. The newly introduced text to speech capabilities also seem highly promising.”

AllegroGraph Named to DBTA’s 100 Companies That Matter Most in Data

AllegroGraph was also recently named to DBTA’s 100 Companies That Matter Most in Data.  The DBTA   100 showcases organizations that delivering solutions for customers to meet the need for real-time, data-driven insights.

Franz Knowledge Graph Technology and Services

Franz’s Knowledge Graph Solution includes both technology and services for building industrial strength Entity-Event Knowledge Graphs based on best-of-class tools, products, knowledge, skills and experience. At the core of the solution is Franz’s graph database technology, AllegroGraph with FedShard, which is utilized by dozens of the top F500 companies worldwide and enables businesses to extract sophisticated decision insights and predictive analytics from highly complex, distributed data that cannot be uncovered with conventional databases.

Franz delivers the expertise for designing ontology and taxonomy-based solutions by utilizing standards-based development processes and tools. Franz also offers data integration services from siloed data using W3C industry standard semantics, which can then be continually integrated with information that comes from other data sources. In addition, the Franz data science team provides expertise in custom algorithms to maximize data analytics and uncover hidden knowledge.

About Franz Inc.

Franz Inc. is an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology with expert knowledge in developing and deploying Knowledge Graph solutions. The foundation for Knowledge Graphs and AI lies in the facets of semantic technology provided by AllegroGraph with FedShard and Allegro CL.  The ability to rapidly integrate new knowledge is the crux of the Knowledge Graph and Franz Inc. provides the key technologies and services to address your complex challenges.  Franz Inc. is your Knowledge Graph technology partner.

All trademarks and registered trademarks in this document are the properties of their respective owners.




Knowledge graphs enhance customer experience through speed and accuracy

KMWorld’s recent article covers AllegroGraph and Franz’s customer N3 Solutions.

The Full Article – KMWorld

Knowledge graphs are a way to model enterprise knowledge and represent complex interrelationships in data. Information stored in a graph database can enable rapid retrieval of well-targeted results and provide insights into customers’ interests and needs. Gartner predicts a 100% per-year growth in applications for graph analytics and databases for the next several years. Although knowledge graphs have been deployed by major companies such as Google, Amazon, and LinkedIn due to their ability to incorporate relationships in their analyses as well as their speed, only in the last 5 years has their use become more widespread.

N3 is an outsourced sales company for major organizations that sell complex B2B software, hardware, and tech solutions. It supports businesses in 92 countries, provides services in 25 languages, and holds thousands of hours of conversations every month with customers and prospects. “In today’s world of complex products, it takes a well-educated team to tell the story about how this technology can help a company become more competitive,” said Shannon Copeland, COO of N3. “The sales team needs to be able to instantly access the information they need to do their job.”

Faster insights

The company has been operating for 16 years, and in the last few years began an initiative to manage its knowledge in a more intentional way. “We generate a great deal of data,” noted Copeland, “and we wanted to make more effective use of it to understand our customers. And because of the speed at which business is transacted now, we needed to get insights right away, not a month later in a report.”

N3 built a data model to reflect the essential data elements and the associations among them and decided that a knowledge graph was the best way to represent the information. After looking into partner options, N3 chose to work with Franz, Inc., which provides a semantic graph database called AllegroGraph. “We decided to work with Franz because of its extensive experience and the fact that it had worked with a variety of industries,” Copeland said.

The system built by N3 allows sales teams to organize signals from the market in a way that allows them to better explain the products to prospective buyers. “We build relationships with tech buyers on behalf of our clients,” continued Copeland. “Our employees are typically college graduates who would like to begin their careers in sales and marketing in tech solutions. They take ownership of their territory and we help them be as sophisticated as a future CMO would be.” The resources supplied by the knowledge graph provide the support the sales team needs to tailor information to each prospective customer.

The specific expertise required by the team varies depending on the products being sold, the geographic region, and other factors, and the knowledge graph supports these needs. For example, if a team in southern Portugal needs to know the preferences of that market, the associations built into the graph database can provide the information that is essential for them. “The information we can access helps customers understand the answers to their questions very quickly,” Copeland commented. “We believe the experience that the customers have helps them scope out what they need and what the road map might be.”

The strength of graph databases

A graph databases is a type of NoSQL database that stores data according to associations among data elements rather than in the rows and columns of a relational database. Because graph databases use a dynamic schema rather than a fixed, table-based one, adding new data types and categories is much easier. And because they are semantics-based, graph databases have strengths in inferring intent, producing answers to questions, and making recommendations. They can also make inferences about possible associations from existing associations.

A graph database also provides much more context than a relational database and therefore can return more relevant results when a user is searching; they also integrate data from multiple sources. “At one telecom company we worked with, customer service reps might have [had] to open 15 databases to find out what went wrong and what the solution was,” said Jans Aasman, CEO of Franz. “We took their core customer data, billing information, every CRM call, and every action and put them into AllegroGraph, and the customer service reps were finally able to respond in a meaningful way, whether that was to make an offer to the customer or provide appropriate technical support.” The capability of graph databases to overcome silos and provide an integrated view of the customer is one of its strengths.

In order to create the graph database on which the knowledge graph is built, the relationships among entities need to be mapped. In the case of a hospital patient, the patient is the core entity, and the events are medical encounters or lab results, which may come out of different databases or a data warehouse. “The mapping is a major project, but it only needs to be done once,” Aasman pointed out. “After that, the relationships do not need to be regenerated during the search because they are indexed in AllegroGraph, which makes retrieval very rapid.”




AllegroGraph Named to 100 Companies That Matter Most in Data

Franz Inc. Acknowledged as a Leader for Knowledge Graph Solutions

Lafayette, Calif., June 23, 2020 — Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Semantic Graph Database technology for Knowledge Graph Solutions, today announced that it has been named to The 100 Companies That Matter in Data by Database Trends and Applications.  The annual list reflects the urgency felt among many organizations to provide a timely flow of targeted information. Among the more prominent initiatives is the use of AI and cognitive computing, as well as related capabilities such as machine learning, natural language processing, and text analytics.   This list recognizes companies based on their presence, execution, vision and innovation in delivering products and services to the marketplace.

“We’re excited to announce our eighth annual list, as the industry continues to grow and evolve,” remarked Thomas Hogan, Group Publisher at Database Trends and Applications. “Now, more than ever, businesses are looking for ways transform how they operate and deliver value to customers with greater agility, efficiency and innovation. This list seeks to highlight those companies that have been successful in establishing themselves as unique resources for data professionals and stakeholders.”

“We are honored to receive this acknowledgement for our efforts in delivering Enterprise Knowledge Graph Solutions,” said Dr. Jans Aasman, CEO, Franz Inc. “In the past year, we have seen demand for Enterprise Knowledge Graphs take off across industries along with recognition from top technology analyst firms that Knowledge Graphs provide the critical foundation for artificial intelligence applications and predictive analytics.

Our recent launch of AllegroGraph 7 with FedShard, a breakthrough that allows infinite data integration to unify all data and siloed knowledge into an Entity-Event Knowledge Graph solution will catalyze Knowledge Graph deployments across the Enterprise.”

Gartner recently released a report “How to Build Knowledge Graphs That Enable AI-Driven Enterprise Applications” and have previously stated, “The application of graph processing and graph databases will grow at 100 percent annually through 2022 to continuously accelerate data preparation and enable more complex and adaptive data science.” To that end, Gartner named graph analytics as a “Top 10 Data and Analytics Trend” to solve critical business priorities. (Source: Gartner, Top 10 Data and Analytics Trends, November 5, 2019).

“Graph databases and knowledge graphs are now viewed as a must-have by enterprises serious about leveraging AI and predictive analytics within their organization,” said Dr. Aasman “We are working with organizations across a broad range of industries to deploy large-scale, high-performance Entity-Event Knowledge Graphs that serve as the foundation for AI-driven applications for personalized medicine, predictive call centers, digital twins for IoT, predictive supply chain management and domain-specific Q&A applications – just to name a few.”

Forrester Shortlists AllegroGraph

AllegroGraph was shortlisted in the February 3, 2020 Forrester Now Tech: Graph Data Platforms, Q1 2020 report, which recommends that organizations “Use graph data platforms to accelerate connected-data initiatives.” Forrester states, “You can use graph data platforms to become significantly more productive, deliver accurate customer recommendations, and quickly make connections to related data.”

Bloor Research covers AllegroGraph with FedShard

Bloor Research Analyst, Daniel Howard noted “With the 7.0 release of AllegroGraph, arguably the most compelling new capability is its ability to create what Franz refers to as “Entity-Event Knowledge Graphs” (or EEKGs) via its patented FedShard technology.” Mr. Howard goes on to state “Franz clearly considers this a major release for AllegroGraph. Certainly, the introduction of an explicit entity-event graph is not something I’ve seen before. The newly introduced text to speech capabilities also seem highly promising.”

AllegroGraph Named to KMWorld’s 100 Companies That Matter in Knowledge Management

AllegroGraph was also recently named to KMWorld’s 100 Companies That Matter in Knowledge Management.  The KMWorld 100 showcases organizations that are advancing their products and capabilities to meet changing requirements in Knowledge Management.

Franz Knowledge Graph Technology and Services

Franz’s Knowledge Graph Solution includes both technology and services for building industrial strength Entity-Event Knowledge Graphs based on best-of-class tools, products, knowledge, skills and experience. At the core of the solution is Franz’s graph database technology, AllegroGraph with FedShard, which is utilized by dozens of the top F500 companies worldwide and enables businesses to extract sophisticated decision insights and predictive analytics from highly complex, distributed data that cannot be uncovered with conventional databases.

Franz delivers the expertise for designing ontology and taxonomy-based solutions by utilizing standards-based development processes and tools. Franz also offers data integration services from siloed data using W3C industry standard semantics, which can then be continually integrated with information that comes from other data sources. In addition, the Franz data science team provides expertise in custom algorithms to maximize data analytics and uncover hidden knowledge.

 




Ubiquitous AI Demands A New Type Of Database Sharding

Forbes published the following article by Dr. Jans Aasman, Franz Inc.’s CEO.

The notion of sharding has become increasingly crucial for selecting and optimizing database architectures. In many cases, sharding is a means of horizontally distributing data; if properly implemented, it results in near-infinite scalability. This option enables database availability for business continuity, allowing organizations to replicate databases among geographic locations. It’s equally useful for load balancing, in which computational necessities (like processing) shift between machines to improve IT resource allocation.

However, these use cases fail to actualize sharding’s full potential to maximize database performance in today’s post-big data landscape. There’s an even more powerful form of sharding, called “hybrid sharding,” that drastically improves the speed of query results and duly expands the complexity of the questions that can be asked and answered. Hybrid sharding is the ability to combine data that can be partitioned into shards with data that represents knowledge that is usually un-shardable.

This hybrid sharding works particularly well with the knowledge graph phenomenon leveraged by the world’s top data-driven companies. Hybrid sharding also creates the enterprise scalability to query scores of internal and external sources for nuanced, detailed results, with responsiveness commensurate to that of the contemporary AI age.

 

Read the full article at Forbes.