Franz Inc. Enhances AllegroGraph’s Neuro-Symbolic AI Features with Support for Additional AI Models

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AllegroGraph - Franz Inc.

AllegroGraph – Franz Inc.

AllegroGraph - Voted Best Knowledge Graph

AllegroGraph – Voted Best Knowledge Graph

AllegroGraph’s Ollama Support Delivers New Options for Neuro-Symbolic AI Solutions in the Enterprise

LAFAYETTE, CA, UNITED STATES, November 19, 2024 /EINPresswire.com/ — Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Graph Database technology for Neuro-Symbolic AI Solutions, today announced AllegroGraph 8.3, with support for additional AI models offered via Ollama. This latest release strengthens AllegroGraph’s position as a critical technology for enterprises seeking to integrate advanced AI capabilities with Knowledge Graph-driven solutions.

“AllegroGraph was the first to deliver a comprehensive Neuro-Symbolic AI platform and with the additional options of AI models, enterprise users have the flexibility to use models that best fit their use cases,” said Dr. Jans Aasman, CEO of Franz Inc. “Organizations across a range of industries realize the critical role that Knowledge Graphs play in creating the next generation of AI-driven applications. AllegroGraph provides enterprise users with the trust, explainability, and semantics required to future-proof AI systems.”

“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

As the first Neuro-Symbolic AI Platform, AllegroGraph combines Machine Learning (statistical AI) with knowledge and reasoning (symbolic AI) capabilities. This powerful combination enables AllegroGraph to solve complex problems that require reasoning and learn efficiently with less data, thereby expanding applicability across a broad array of tasks. The blending of machine learning and reasoning in AllegroGraph also produces decisions that are understandable to humans and explainable, an important step in the progression of AI.

The advancements in AllegroGraph encompass the following transformative capabilities and enhancements.

ChatStream – Natural Language Queries with Graph RAG and Feedback – 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.

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.’ AllegroGraph’s ‘triple-attributes’ mechanism puts security ‘in’ the data elements itself. AllegroGraph offers the ability to annotate individual triples or text fragments and thus provides the most granular access method of any Graph-Vector platform.

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.

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

Enhanced Scalability and Performance – AllegroGraph includes enhanced FedShard™ capabilities making the management of sharding more straightforward and user-friendly while reducing query response time and improving overall system performance.

Advanced Knowledge Graph Visualization – A new version of Franz’s industry-leading graph visualization software, Gruff v9, is integrated into AllegroGraph. Gruff now includes the ChatStream Natural Language Query feature as a new means to query your Knowledge Graph and is the only graph visualization tool that illustrates RDF-Star (RDF*) annotations, enabling users to add descriptions to edges in a graph – such as scores, weights, temporal aspects and provenance.

Conference Presentations
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. 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. https://www.text-analytics-forum.com/2024/Default.aspx

These presentations build upon recent research efforts by Franz Inc. in a recent paper – “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/

Industry Recognition
Franz’s AllegroGraph was recently awarded “Best Knowledge Graphs” by KMWorld Reader’s Choice voting. Franz was also voted as a finalist in the “Best AI” and “Best Text Analytics and NLP” Reader’s Choice voting. Franz was also named to the 2024 – “Artificial Intelligence 100” by KMWorld magazine.

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.
+1 510-452-2000
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