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Speaker

Manuel Maguga Darbinian

Manuel Maguga Darbinian

AI & product Lead at Boundless Digital | Founder of Spiintel

Amsterdam, The Netherlands

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My name is Manuel, AI & product Specialist with business background. I started my AI & Graph experience back in Klarna during the company wide initiative to build the so-called "Best Knowledge Management System" powered by Neo4J and GenAI.

After Klarna I embarked in an exciting journey as a consultant, learning about organisation pain-points and advising on solutions and way forward.

After compounding all these learnings, I started off Spiintel as a side project. Currently I'm leading and supporting Boundless in developing cabyn.ai, a marketing tool aimed at bridging marketing data & analysis with content creation in order to enhance ranking and SEO.

A funny fact about myself: I did not know how to code 4 years ago, thanks to AI and own interest, I have been learning Python and best practices in infrastructure building. I'm now deep into tech and coding my way forward.

Area of Expertise

  • Business & Management
  • Information & Communications Technology

From Static to Living Intelligence: Building an AI-Ready Temporal Graph with Spiintel

Most organisations still rely on static, fragmented knowledge: documents spread across drives, Slack, inboxes, or internal wikis. Over time, this information decays, diverges, and loses context, while AI systems are expected to reason over it. The result is costly AI pipelines, unreliable insights, and decisions made on incomplete or outdated intelligence.

In this session, I will show how Spiintel transforms fragmented organisational knowledge into a living, evolving intelligence layer. Instead of treating knowledge as static documents, Spiintel models it as a temporal, ontology-driven graph that humans and AI collaboratively build, maintain, and reason from.

Built on Neo4j, Spiintel enables organisations to:
- Define and evolve their ontology through a dedicated META subgraph
- Enrich the knowledge graph using natural language and file ingestion
- Autonomously resolve duplicates while preserving full historical context
- Retrieve insights through hybrid search and Text2Cypher, grounded in structured intelligence rather than raw text

I will walk through Spiintel’s three core components: META Subgraph, Enrich, and Retrieve. I will demonstrate how they work together to solve real-world challenges such as schema evolution, entity resolution, temporal tracking, and inconsistent data structures. Using simple natural language, knowledge can be created, updated, merged, and queried while the system maintains a complete, auditable history.

By the end of the session, you’ll understand:
- How to design and evolve a temporal knowledge graph that mirrors how your organisation actually works
- How natural-language-driven CRUD and ingestion enable continuous intelligence building
- Why ontology-first, AI-native architectures reduce integration cost and improve model performance
- How graph-native retrieval enables fast, context-rich insights for both humans and AI

If your teams are struggling with siloed knowledge, brittle RAG pipelines, or AI systems that don’t scale with organisational complexity, this talk will show how to build a connected, self-evolving intelligence layer using graph technology.

Manuel Maguga Darbinian

AI & product Lead at Boundless Digital | Founder of Spiintel

Amsterdam, The Netherlands

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