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Gartner Says Lack of Semantics Causes Inaccurate AI Agents and Wasted Spending. #AllegroGraph provides the semantic foundation for governed, context-aware, explainable AI with enterprise #KnowledgeGraphs at the core of #AgenticAI. #AI #SemanticAI buff.ly/uMUKBEm
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AllegroGraph v9 is here — and it introduces GraphTalker, a major advancement in how people and AI agents interact with enterprise Knowledge Graphs. GraphTalker brings natural-language intelligence directly to the #semanticlayer. buff.ly/tdBJ7hW #KnowledgeGraphs #NSAI
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AllegroGraph 8.5: Strengthening the Semantic Foundation for Agentic AI AllegroGraph is a Neuro-Symbolic AI Platform that fuses machine learning (statistical AI) with symbolic AI, enabling it to solve complex problems with fewer data and provide explainable outcomes. The latest release announced today, AllegroGraph v8.5, aims to help enterprises build Agentic AI solutions by enabling more intuitive, human-like interaction between users and intelligent systems—critical for agents that need to reason, plan, and act autonomously. AllegroGraph v8.5 combines knowledge graphs, vector embeddings, and neuro-symbolic reasoning to provide the semantic layer needed for AI agents to interpret data meaningfully and deliver more accurate, explainable results. New capabilities include: * Optimized Natural Language Query (NLQ): Faster, more token-efficient translation of natural language questions into graph queries, reducing LLM usage while improving response times. * Expanded MCP Support: Simplifies connecting models, tools, and enterprise knowledge graph workflows into agentic AI systems. * Faster Vector Processing: Accelerates vector creation and supports configurable vector sizes to optimize performance and cost. * Enhanced Observability: Enhanced integration with Prometheus and Grafana for improved monitoring and operational visibility. * Production-ready AI Semantic Graph Infrastructure: Strengthens AllegroGraph’s role as a production-ready platform for AI applications that combine knowledge graphs, vector search, and LLM reasoning. @Franzinc was recently listed as a Neuro-Symbolic AI vendor in Gartner’s 2025 Hype Cycle for AI in recognition of AllegroGraph’s Neuro-Symbolic AI capabilities. According to Gartner, “Neurosymbolic AI 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. The neurosymbolic approach leads to more powerful, versatile and interpretable AI solutions and allows AI systems to reason through more complex tasks. Generative AI systems are starting to leverage neurosymbolic methods to overcome their reasoning shortcomings.” Source: Gartner, Hype Cycle for Artificial Intelligence, July 2025. “AI requires structured knowledge,” said Charles Betz, VP Principal Analyst at Forrester. “GenAI and large language models (LLMs) require structured and contextualized data. Graphs provide a foundational knowledge model that enhances AI-driven automation, reasoning, and prediction. If unstructured data and the LLMs and vector databases that make sense of it are like flesh, graphs are the skeleton, the bones that give it structure. You need both.” Source: Forrester, The Graphic Future of IT Management, March 2025. -- The Year of the Graph's Spring 2026 newsletter issue on all things #KnowledgeGraph, #GraphDB, Graph #Analytics / #DataScience / #AI and #SemTech is coming soon. Subscribe and follow to be in the know. Reach out if you'd like to be featured 👇 yearofthegraph.xyz/newslette…
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19 Dec 2025
Proud to share that AllegroGraph has been named a DBTA Trend-Setting Product for 2026. Knowledge Graphs Neuro-Symbolic AI are becoming foundational to explainable, accountable AI—honored to be recognized. #KnowledgeGraphs #NeuroSymbolicAI #AgenticAI buff.ly/Eo9J83D
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26 Nov 2025
On the day before Thanksgiving, we’re especially grateful to everyone who helped #AllegroGraph win 2025 Best Knowledge Graph in the KMWorld Readers’ Choice Awards! Thank you to our customers, partners, and community. buff.ly/64KgmVz
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Recording Available - Webinar – Building Accountable AI Agents with Knowledge Graphs - AllegroGraph buff.ly/mEM2mDK #KnowledgeGraphs #NeuroSymbolicAI #Graphs #AllegroGraph
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22 Oct 2025
Replying to @_devJNS
Yeah, I agree! 💯 MongoDB is great, but there are some better ones. Here’s a short list off the top of my mind: MySQL PostgreSQL MariaDB Oracle Database Microsoft SQL Server IBM Db2 SQLite Amazon Aurora Google Cloud SQL CockroachDB YugabyteDB TiDB OceanBase SingleStore Altibase NuoDB InterBase Firebird SAP HANA SAP ASE Informix Teradata Greenplum Vertica Exasol Snowflake Redshift BigQuery DuckDB H2 Apache Derby Apache Ignite VoltDB Redis Aerospike Riak KV DynamoDB FoundationDB Tarantool Berkeley DB RocksDB LevelDB BadgerDB LMDB Kyoto Cabinet HyperLevelDB WiredTiger EventStoreDB Apache Cassandra ScyllaDB HBase Google Bigtable Azure Cosmos DB Hypertable Accumulo CouchDB Couchbase RethinkDB RavenDB ArangoDB OrientDB MarkLogic BaseX eXist-db ZODB Neo4j JanusGraph TigerGraph Dgraph Amazon Neptune Blazegraph AllegroGraph AnzoGraph Faunus InfiniteGraph InfluxDB TimescaleDB QuestDB OpenTSDB Prometheus VictoriaMetrics Graphite Kdb Apache IoTDB DalmatinerDB RRDtool M3DB TDengine Elasticsearch OpenSearch Solr Splunk Rockset ClickHouse Apache Druid Apache Pinot Apache Kylin Memcached Hazelcast Oracle TimesTen TIBCO ActiveSpaces HSQLDB Realm LiteDB TinyDB NeDB ObjectBox PouchDB IndexedDB LocalStorage Google Firestore Google Cloud Spanner CockroachDB Cloud Yugabyte Cloud Neon PlanetScale AlloyDB MarkLogic FoundationDB Datastax Enterprise db4o ObjectDB GemStone/S Versant Object Database PostGIS SpatiaLite Oracle Spatial GeoMesa GeoWave MonetDB CrateDB Apache Hudi Apache Iceberg Delta Lake Datomic Firebase Realtime Database GridDB Machbase TileDB
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Gartner - By 2027, organizations that prioritize semantics in AI-ready data will increase their GenAI model accuracy by up to 80% and reduce costs by up to 60%. Poor semantics in GenAI lead to greater hallucinations... buff.ly/5cBmvVc #AllegroGraph #NeuroSymbolicAI
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🚨Neuro-Symbolic AI? And what’s AllegroGraph?🚨
Neuro-Symbolic AI with AllegroGraph The emerging paradigm of Neuro-Symbolic Artificial Intelligence (AI) stems from the recent efforts to enhance statistical AI (machine learning, LLMs) with the complementary capabilities of Symbolic AI (knowledge and reasoning, Knowledge Graphs). allegrograph.com/products/ne… AllegroGraph is a Horizontally Distributed, Multi-model (Vector, Document and Graph), Entity-Event Knowledge Graph platform that enables businesses to build Neuro-Symbolic AI applications capable of extracting sophisticated decision insights and predictive analytics from their highly complex, distributed data that can’t be answered with only Generative AI. FedShard™ Speeds Complex Queries through a patented in-memory federation function, the results from each machine are combined so that the query process appears as if only one database is being accessed, although many different databases and data stores and knowledge bases are actually being accessed and returning results. This unique data federation capability accelerates results for highly complex queries across highly distributed data sets and knowledge bases. Unlike traditional relational databases or simple property graph databases, Franz’s product AllegroGraph employs a combination of document (JSON and JSON-LD) Vector (Generation and storage), and graph technologies that process data with contextual and conceptual intelligence. Knowledge Graphs built on the AllegroGraph platform are able to run queries of unprecedented complexity to support predictive analytics that help companies make better, real-time decisions. allegrograph.com/products/al… RDF-star and SPARQL-star The Resource Description Framework (RDF) is a general-purpose framework for representing information on the Web. RDF-star extends RDF with a convenient way to make statements about other statements. This specification defines the abstract syntax of RDF-star as an extension of RDF's. It extends a number of RDF concrete syntaxes to support the new abstract syntax. It also extends RDF's formal semantics. Finally, this specification extends the SPARQL language to allow querying and updating of RDF-star data. w3c.github.io/rdf-star/cg-sp… RDF & SPARQL (RDF-star) Working Group The mission of the RDF & SPARQL Working Group is to update and maintain the set of RDF and SPARQL related recommendations, extending them with the ability to concisely represent and query statements about statements. w3.org/groups/wg/rdf-star/ AllegroGraph 8.4.0 RDF-star Support RDF-star (or RDF*) allows marking up triple with meta information such as source, quality, believability, or other attributes, thus extending the RDF graph model by including statements about statements. The main part of the RDF-star specification is the concept of quoted triple, where quoted has similar meaning to quotation in Lisp. AllegroGraph provides opt-in support for RDF-star semantics on per-repository basis. AllegroGraph supports loading and exporting RDF-star data in the following RDF-star formats: Turtle-star; TriG-star; N-Triples-star; N-Quads-star; NQX-star Since RDF-star is likely to become part of RDF-1.2 specs, these formats are not treated as separate syntaxes. Instead, when an AllegroGraph repository has RDF-star semantics enabled, the standard parsers and serializers will automatically handle RDF-star data. franz.com/agraph/support/doc…
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Neuro-Symbolic AI with AllegroGraph The emerging paradigm of Neuro-Symbolic Artificial Intelligence (AI) stems from the recent efforts to enhance statistical AI (machine learning, LLMs) with the complementary capabilities of Symbolic AI (knowledge and reasoning, Knowledge Graphs). allegrograph.com/products/ne… AllegroGraph is a Horizontally Distributed, Multi-model (Vector, Document and Graph), Entity-Event Knowledge Graph platform that enables businesses to build Neuro-Symbolic AI applications capable of extracting sophisticated decision insights and predictive analytics from their highly complex, distributed data that can’t be answered with only Generative AI. FedShard™ Speeds Complex Queries through a patented in-memory federation function, the results from each machine are combined so that the query process appears as if only one database is being accessed, although many different databases and data stores and knowledge bases are actually being accessed and returning results. This unique data federation capability accelerates results for highly complex queries across highly distributed data sets and knowledge bases. Unlike traditional relational databases or simple property graph databases, Franz’s product AllegroGraph employs a combination of document (JSON and JSON-LD) Vector (Generation and storage), and graph technologies that process data with contextual and conceptual intelligence. Knowledge Graphs built on the AllegroGraph platform are able to run queries of unprecedented complexity to support predictive analytics that help companies make better, real-time decisions. allegrograph.com/products/al… RDF-star and SPARQL-star The Resource Description Framework (RDF) is a general-purpose framework for representing information on the Web. RDF-star extends RDF with a convenient way to make statements about other statements. This specification defines the abstract syntax of RDF-star as an extension of RDF's. It extends a number of RDF concrete syntaxes to support the new abstract syntax. It also extends RDF's formal semantics. Finally, this specification extends the SPARQL language to allow querying and updating of RDF-star data. w3c.github.io/rdf-star/cg-sp… RDF & SPARQL (RDF-star) Working Group The mission of the RDF & SPARQL Working Group is to update and maintain the set of RDF and SPARQL related recommendations, extending them with the ability to concisely represent and query statements about statements. w3.org/groups/wg/rdf-star/ AllegroGraph 8.4.0 RDF-star Support RDF-star (or RDF*) allows marking up triple with meta information such as source, quality, believability, or other attributes, thus extending the RDF graph model by including statements about statements. The main part of the RDF-star specification is the concept of quoted triple, where quoted has similar meaning to quotation in Lisp. AllegroGraph provides opt-in support for RDF-star semantics on per-repository basis. AllegroGraph supports loading and exporting RDF-star data in the following RDF-star formats: Turtle-star; TriG-star; N-Triples-star; N-Quads-star; NQX-star Since RDF-star is likely to become part of RDF-1.2 specs, these formats are not treated as separate syntaxes. Instead, when an AllegroGraph repository has RDF-star semantics enabled, the standard parsers and serializers will automatically handle RDF-star data. franz.com/agraph/support/doc…
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It is a foundational flaw in Gen AI and as any data scientist knows, bad training data makes for bad and error prone outputs. Shows the need for some classic symbolic AI. Is there some real good neuro-symbolic AI being built? Think it's needed! Source: AllegroGraph
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21 Mar 2024
We hope to see you in Orlando at Enterprise Data World, March 24-29. Presentation - "Using Knowledge Graphs and LLMs for Deep Entity Exploration" - #NeuroSymbolicAI #KnowledgeGraph #AllegroGraph #EDW24 buff.ly/3NfkByF
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21 Feb 2024
Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar). If you missed our recent webinar, we welcome you to watch the full recording at buff.ly/3SJvhYt. Slides in the description or linked here buff.ly/3SIGys5 #neurosymbolicai
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5 Feb 2024
Join us February 7 at 10AM Pacific for an enlightening webinar to explore the groundbreaking features of #AllegroGraph 8.0, the latest revolution in Enterprise #KnowledgeGraphs and #Neuro-SymbolicAI. - Register buff.ly/3OxmWpE
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"AllegroGraph is a python-users dream for working with graph data for analytics and ML.Ontologists will have a blast exploring their hard work through the Gruff that sits on top of the multimodal database (OWL, document and vector store, LLMs, and KGs)" buff.ly/4aBgw25
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Neuro-Symbolic AI with AllegroGraph: LLM RAG Knowledge Graph VectorStore Rules - All in one platform allegrograph.com/products/ne… triple-store queried using SPARQL and Prolog, RDFS OWL predicates for reasoning
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AllegroGraph v8 > a groundbreaking Neuro-Symbolic #AI Platform that incorporates Large Language Model (#LLM) components directly into #SPARQL along with vector generation and vector storage for a comprehensive AI Knowledge Graph solution. allegrograph.com/new-allegro… #lisp
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