Franz’s Knowledge Graph-Driven Neuro-Symbolic AI Platform Delivers Grounded AI Solutions for the Enterprise

LAFAYETTE, CA, UNITED STATES, November 13, 2024 /EINPresswire.com/ -- Franz Inc., an early innovator in Artificial Intelligence (AI) and leading provider of Graph Database technology for Neuro-Symbolic AI Solutions, today announced that it’s flagship platform, AllegroGraph, was voted the “Best Knowledge Graph” in the 2024 KMWorld Readers’ Choice Awards.

This recognition follows Franz’s release of AllegroGraph v8 earlier this year, the first Neuro-Symbolic AI Platform to integrate Knowledge Graphs, Symbolic AI, Machine Learning, and Vector Storage, while guiding Generative AI via Retrieval Augmented Generation (RAG) to supply LLMs with source-of-truth data and prevent hallucinations.

"We are delighted by this recognition from the Graph Community, which underscores our unwavering dedication in advancing the critical role that Knowledge Graphs play in creating the next generation of AI-driven applications," said Dr. Jans Aasman, CEO, Franz Inc. “Neuro-Symbolic AI represents the next evolution of artificial intelligence, where the integration of symbolic reasoning with machine learning delivers unparalleled accuracy, interpretability, and versatility. This approach advances AI technology and ensures that complex decision-making processes are transparent and reliable, setting new benchmarks for the industry.”

“Neuro-Symbolic AI is important because it addresses limitations in current AI systems, such as incorrect outputs, lack of generalization to a variety of tasks and an inability to explain the steps that led to an output,” according to Gartner, a leading global research and advisory firm. “This leads to more powerful, versatile and interpretable AI solutions and allows AI systems to tackle more complex tasks with humanlike reasoning.” Source: Gartner, Hype Cycle for Artificial Intelligence, 2024.

“The two biggest movers on this year’s Hype Cycle are AI engineering and knowledge graphs,” points out Afraz Jaffri, Senior Director Analyst, KI Leader at Gartner. “Knowledge graphs are machine-readable representations of the physical and digital worlds. They capture information in a visually intuitive format, yet are still able to represent complex relationships. More importantly, they provide dependable logic and explainable reasoning (as opposed to GenAI’s fallible but powerful predictive capabilities).” Source: Gartner, Explore Beyond GenAI on the 2024 Hype Cycle for Artificial Intelligence

Franz’s Neuro-Symbolic AI platform AllegroGraph offers the following suite of groundbreaking capabilities.

ChatStream – Stateful Bot Technology - ChatStream harnesses the power of natural language processing to query Knowledge Graph data (Graph RAG) within AllegroGraph. This innovative feature transforms data analysis by allowing users to explore data through simple questions without writing graph queries. ChatStream leverages AllegroGraph’s Neuro-symbolic AI capabilities to unlock valuable insights from data, setting a new standard in the ease of accessing and interpreting information.

Retrieval Augmented Generation (RAG) for LLMs - AllegroGraph guides Generative AI content through RAG, feeding LLMs with the ‘source of truth.’ This innovative approach helps avoid ‘hallucinations’ by grounding the output in fact-based knowledge. As a result, organizations can confidently apply these insights to critical decision-making processes, secure in the knowledge that the information is both reliable and trustworthy.

Enterprise Document Deep-insight - VectorStore capabilities within AllegroGraph offer a seamless bridge between enterprise documents and Knowledge Graphs. This unique feature empowers users to access a wealth of knowledge hidden within documents, allowing users to query content that was previously considered 'dark data.’ Users gain a comprehensive view of enterprise data, contributing to the business's deeper insights from its proprietary data.

AI Symbolic Rule Generation - AllegroGraph offers built-in rule-based system capabilities tailored for symbolic reasoning. This unique feature distills complex data into actionable, interpretable rules. AI symbolic rule generation enables predictions or classifications based on data and provides transparent explanations for their decisions by expressing them in symbolic rules, enhancing trust and interpretability in AI systems.

Unparalleled Graph-Vector Security – The Triple Attributes mechanism in AllegroGraph puts security ‘in’ the data elements itself. Users can annotate individual triples or text fragments and thus provide the most granular access method of any Graph-Vector platform.

Knowledge Graph-as-a-Service – A new hosted, free version grants users access to the power of AllegroGraph with ChatStream via a convenient web login - https://allegrograph.cloud

Conference Presentations
Dr. Aasman will deliver a presentation on “Knowledge Graph-Driven Neuro-Symbolic System for Intelligent Document Matching” at the International Semantic Web Conference on November 14, 2024. This session will explore cutting-edge advancements in leveraging knowledge graphs and neuro-symbolic AI for enhanced document matching. For more details: https://iswc2024.semanticweb.org/

On November 21, 2024, Dr. Aasman will present “Bring Your A(I) Game to Knowledge & Content Activation” at the KMWorld Conference, where he will explore innovative approaches to activating knowledge and content with AI-driven solutions. For more details: https://www.kmworld.com/Conference/2024/Default.aspx

Also on November 21, 2024, Dr. Aasman will present “Intelligent Terminology Matching Using a Knowledge Graph and Vector Database” at the Text Analytics Forum highlighting the synergy between knowledge graphs and vector databases for enhanced terminology matching. For more details: https://www.text-analytics-forum.com/2024/Default.aspx

These presentations build upon recent research efforts by Dr. Aasman and his colleagues. In a paper co-authored by Richard Wallace, Ravi Bajracharya, Jans Aasman and Craig Norvell, they explored “Pruning Cycles in UMLS Metathesaurus: A Neuro Symbolic AI Approach,” which was featured at the NLP4KGC: 3rd International Workshop on Natural Language Processing for Knowledge Graph Creation. For more details: https://allegrograph.com/pruning-cycles-in-umls-metathesaurus-a-neuro-symbolic-ai-approach/

About Franz, Inc.
Franz Inc. stands at the forefront of AI innovation, offering Neuro-Symbolic AI solutions that transform complex data into actionable and comprehensible insights. The company’s flagship platform, AllegroGraph, merges the analytical strength of deep learning with the precision of logical reasoning, establishing itself as a critical resource for Enterprises aiming to capitalize on the latest advancements in AI technology. Catering to an array of needs from intricate data integration and cutting-edge analytics to the creation of dynamic Knowledge Graphs, Franz Inc. delivers potent, scalable, and accessible solutions designed to navigate the complexities of today’s data-driven environments.

Craig Norvell
Franz Inc.
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Neuro-Symbolic AI with AllegroGraph

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