• By Franz Inc.
  • 27 June, 2024

Franz Inc. Enhances ChatStream to Include Graph RAG with Feedback to Power Stateful Natural Language Queries in AllegroGraph

ChatStream with AllegroGraph’s Neuro-Symbolic AI Capabilities Unlocks Contextual Enterprise Knowledge through Text Queries with Long-term Memory

Lafayette, Calif., June 27, 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 8.2, a groundbreaking Neuro-Symbolic AI Platform with enhancements to ChatStream™ offering users a natural language query interface that provides more accurate and contextually relevant responses.  ChatStream’s Graph RAG with Feedback enables more accurate, context-aware, and continuously evolving natural language queries, providing stateful and contextually relevant responses.

“AllegroGraph was the first to deliver a comprehensive Neuro-Symbolic AI platform and with the enhancements to ChatStream it is even easier to ask questions of your connected enterprise data and maintain a long-term memory of your conversation history,” 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.

ChatStreamä Natural Language Queries with Graph RAG and Feedback – ChatStream harnesses the power of natural language processing for querying Knowledge Graph data 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.

This enhanced version of ChatStream provides long-term memory of conversation history, also known as ‘Retrieval Augmented Generation with Feedback’, or ‘RAG with Feedback’. The term ‘Feedback’ in this case refers to storing short-term memories of the recent dialog in the long-term memory of the AllegroGraph platform. When responding to a human input, ChatStream draws upon two sources of information, the long- and short-term memory of the conversation with that individual and all the other facts, memories, and experiences in the Knowledge Graph.

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-insightVectorStore 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 –

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 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.

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.