Franz Inc. Unveils ChatStream to Power Natural Language Queries in the AllegroGraph Neuro-Symbolic AI Platform

ChatStream Transforms Data Analysis by Empowering Users to Access Complex Enterprise Knowledge through Simple Questions

Lafayette, Calif., April 22, 2024 — Franz Inc., an early innovator in Artificial Intelligence (AI) and leading supplier of Graph Database technology for Entity-Event Knowledge Graph Solutions, today announced AllegroGraph 8.1, a groundbreaking Neuro-Symbolic AI Platform that incorporates ChatStreamä, a natural language query interface for querying a neuro-symbolic application.  AllegroGraph with ChatStream redefines how Knowledge Graphs are queried and expands the boundaries of what AI can achieve within the most secure graph database on the market.

“AllegroGraph was the first to deliver a comprehensive Neuro-Symbolic AI platform and the addition of ChatStream makes it even easier to ask questions of your connected enterprise data,” said Dr. Jans Aasman, CEO, Franz Inc. “Organizations across a range of industries are realizing 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.”

“Neurosymbolic AI is a form of composite AI that combines machine learning methods and symbolic systems to create more robust and trustworthy AI models. It provides a reasoning infrastructure for solving a wider range of business problems more effectively.” Gartner – Hype Cycle for Artificial Intelligence, 2023

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.

Natural Language Queries with ChatStreamä – ChatStream is a new key feature within AllegroGraph that harnesses the power of natural language processing for querying Knowledge Graph data. 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. One unique feature of AllegroGraph’s vector store implementation is that it lives under the same security framework that we apply to the graphs. 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.

New Web Interface – AllegroGraph includes a striking redesign of its web interface – AGWebView. This fresh look and feel provides users an enhanced and intuitive way to interact with the platform, while co-existing in parallel with the Classic View.

Advanced Knowledge Graph Visualization – A new version of Franz’s industry-leading graph visualization software, Gruff v9, is integrated into AllegroGraph. Gruff v9 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.

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.