Franz Inc.

Neuro-Symbolic AI - Knowledge Graph Solutions

[Franz Inc. @Franzinc]

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. https://t.co/gn6Ubu8elT #KnowledgeGraphs #NSAI

[DBTA Magazine @dbtrends]

Congratulations to @Franzinc on being named as one of the companies that matter most in #Data! https://t.co/YU7rIQ5IGY

[Franz Inc. @Franzinc]

Join the 2026 Data-Centric Architecture Forum, June 9–11. Dr. Aasman presents “The Knowledge Graph as an Agentic Control Plane for Data-Centric Architecture.” Key insights on how #knowledgegraphs drive intelligent systems. #AgenticAI #DCAF #DataCentric https://t.co/DbQVckC9N4

[Franz Inc. @Franzinc]

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 https://t.co/LzQXd95v8y

[Franz Inc. @Franzinc]

Dr. Aasman will be speaking at STIDS 2026 -Semantic Tech for Intelligence, Defense, and Security conference. "Semantic Interoperability in Cybersecurity: Harmonizing Threat Intelligence with gist and gistCyber" #STIDS2026 #KnowledgeGraphs #NeuroSymbolicAI https://t.co/6hJoWNKinW

[Franz Inc. @Franzinc]

Join us at the 2026 Data-Centric Architecture Forum in Fort Collins, June 9–11. Dr. Aasman will present - “The Knowledge Graph as an Agentic Control Plane for Data-Centric Architecture,” #DCAF #KnowledgeGraphs #DataCentric https://t.co/uIFRYd9Xgy

[Franz Inc. @Franzinc]

Dr. Aasman was interviewed for this @KMWorldMagazine article - AI’s Impact on Data Silos and Knowledge Hubs https://t.co/fFOQJ6yiXM #KnowledgeGraphs #NeuroSymbolicAI #ContextGraphs

[The Year of the Graph @TheYotg]

Context Graph Architecture: Why Knowledge Architecture Is the Missing Layer

Context graphs are being called AI's next trillion-dollar opportunity. But before chasing the new label, it's worth asking: what's actually new here?

Forrester's Charles Betz cuts through the noise: EA has maintained entity graphs since Zachman (1987). CMDBs go back to ITIL v1 in the 1990s. APM, process mining, ChatOps, architecture decision records -- these disciplines have been assembling the pieces of a unified context graph in isolation for decades. The graph was never missing. It's fragmented.

George Anadiotis takes the argument further. The decision trace layer -- who decided what, why, under what authority -- isn't absent from organisations. It lives in Slack threads, incident postmortems, Jira tickets, and people's heads. Extracting it and making it queryable is not a database problem. It requires knowledge engineering: observing work practices, interviewing domain experts, encoding tacit reasoning in formal, machine-readable representations.

That's the missing layer. Not the graph itself -- the knowledge architecture that makes it governable.

The infrastructure answer is not exotic either. RDF/OWL provides typed entities and governed relationships. Named graphs handle provenance and versioning. SPARQL enables queryability. These are the building blocks that turn an entity layer from a drawing into something that can actually satisfy governance requirements. Alberto D. Mendoza's conversion of ArchiMate 3.2 to an RDF ontology is a direct, working instantiation of this approach.

On the tooling side: the LLM Wiki pattern -- extracting discrete facts from unstructured sources into a graph, then synthesising into structured queryable form -- is being adopted at scale as a population accelerator for enterprise Agentic AI implementations. The Semantic Web has a 25-year library of patterns, vocabularies and tools to build on.

The key reframe: ontological modeling was never meant to be a runtime. Its value is in defining consistent logic aligned with domain knowledge -- ensuring concepts don't contradict each other across different data schemas.

Entity graphs anchored in EA, EA anchored in knowledge representation, decision traces made queryable: that's context graph architecture grounded in something that can actually hold.

The question isn't whether context graphs are real. It's whether organisations will start building the knowledge architecture they require now, or wait until their competitors have a three-year head start.

By @linked_do

https://t.co/U0bkxg0P69

#KnowledgeArchitecture #EnterpriseArchitecture #ContextGraphs #AgenticAI #Ontology

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[EU Lisp Symposium @elsconf]

#ELS2026 is starting with one of our sponsor's CTO at #Keepit talking about the use of #lisp in a commercial company...

[Franz Inc. @Franzinc]

Dr. Jans Aasman will be participating on the KGC 2026 panel “From Knowledge Graphs to Digital Twins: Are Our Models Ready?”
Join the discussion at #KGC2026, May 4–8 in NYC #KGC2026 #KnowledgeGraphs #DigitalTwins #EnterpriseAI #SemanticAI #NeuroSymbolicAI https://t.co/RWDXOFYA2Y

[Dr. Lance Eliot @LanceEliot]

Neuro-symbolic AI win: https://t.co/QWeJRlgNUX #AI #forbes #techbrium #chatgpt

[Dr. Lance Eliot @LanceEliot]

Neuro-symbolic AI: https://t.co/m8WPyPhWXo #forbes #techbrium #chatgpt

[Gary Marcus @GaryMarcus]

Claude Code is not AGI, but it is the single biggest advance in AI since the LLM.

But the thing is, Claude Code is NOT a pure LLM. And it’s not pure deep learning. Not even close.

And that changes everything.

The source code leak proves it. Tucked away at its center is a 3,167 line kernel called print.ts.

print.ts is a pattern matching. And pattern matching is supposed to be the *strength* of LLMs.

But Anthropic figured out that if you really need to get your patterns right, you can’t trust a pure LLM. They are too probabilistic. And too erratic.

Instead, the way Anthropic built that kernel is straight out of classical symbolic AI. For example, it is in large part a big IF-THEN conditional, with 486 branch points and 12 levels of nesting — all inside a deterministic, symbolic loop that the real godfathers of AI, people like John McCarthy and Marvin Minsky and Herb Simon, would have instantly recognized.*

Putting things differently, Anthropic, when push came to shove, went exactly where I long said the field needed to go (and where @geoffreyhinton said we didn’t need to go): to Neurosymbolic AI.

That’s right, the biggest advance since the LLM was neurosymbolic. AlphaFold, AlphaEvolve, AlphaProof, and AlphaGeometry are all neurosymbolic, too; so is Code Interpreter; when you are calling code, you are asking symbolic AI do an important part of the work.

Claude Code isn’t better because of scaling.

It’s better because Anthropic accepted the importance of using classical AI techniques alongside neural networks — precisely marriage I have long advocated.

It’s *massive* vindication for me (go see my 2019 debate with Bengio for context, or to my 2001 book, The Algebraic Mind), but it still ain’t perfect, or even close.

What we really need to do to get trustworthy AI rather than the current unpredictable “jagged” mess, is to go in the knowledge-, reasoning-, and world-model driven direction I laid out in 2020, in an article called the Next Decade in AI, in which neurosymbolic AI is just the *starting point* in a longer journey.*

Read that article if you want to know what else we need to do next.

The first part has already come to pass. In time, other three will, too.

Meanwhile, the implications for the allocation of capital are pretty massive: smartly adding in bits of symbolic AI can do a lot more than scaling alone, and even Anthropic as now discovered (though they won’t say) scaling is no longer the essence of innovation.

The paradigm has changed.

—
*Claude Code is plainly neurosymbolic but the code part is a mess; as Ernie Davis and I argued in Rebooting AI in 2019, we also need major advances in software engineering. But that’s a story for another day.

[The Year of the Graph @TheYotg]

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.

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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 👇

https://t.co/7pg6gqWYvw

[Franz Inc. @Franzinc]

Weather Shmether - Going to be a great day of talks (Jan 24) - The Future Cognitive OS Uses a Knowledge-Based Semantic Layer - Data Day Texas 2026 Sessions | Data Day Texas https://t.co/XkWPvioG7l

[Franz Inc. @Franzinc]

From ALICE to Neuro-Symbolic AI: A Conversation with Dr. Richard Wallace https://t.co/TgpdKXZsPV

[Franz Inc. @Franzinc]

Collaborative Machine Reasoning Marks AI’s Next Inflection Point - Read our recent article @TheAIInnov - https://t.co/KVpHvLSUUs

[Franz Inc. @Franzinc]

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 https://t.co/3DE6WvaEiE

[Franz Inc. @Franzinc]

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. https://t.co/woWo4bbONg

[KMWorld Magazine @KMWorldMagazine]

Congrats to @Franzinc for winning the #KnowledgeGraphs category for the #KMWorld 2025 Readers' Choice Awards! https://t.co/JuXDOAUxMu