From Fragmented Data to Agent-Ready Context: Building an Ontology-Based Intelligence Layer

Session Track: Knowledge Graphs & GraphRAG

Session Time: 11:00 am - 11:30 am April 15

Session description

As AI becomes increasingly embedded in every workflow, the limiting factor isn’t model (LLM) quality, it’s data.

Organisations operate on fragmented, partially structured knowledge spread across tools, documents, conversations, and workflows. AI automations built on top of this environment inherit inconsistency, fragility, and stale information.

This session introduces Spiintel’s architecture for building an ontology-driven intelligence foundation designed specifically for AI agents.

Rather than treating retrieval as a search problem, Spiintel treats context as infrastructure. Under the hood, unstructured and semi-structured inputs are transformed into a –dynamically, evolving ontology-backed graph. The system maintains historical continuity, enabling agents to reason over not just what is true, but what was true and when.

I will break down the core architectural components:

1) The Data Source layer, which enables the management of the source data by generating/maintaining first a schema/ontology (META Subgraph), and then generating the actual graph on the back of this schema.

2) The Conversational layer (chat), which enables hybrid search and Text2Cypher retrieval

Key technical topics covered:
– Building graph-backed systems that reduce hallucination and improve AI agent reliability
– Semantic and Text2Cypher retrieval

This session is aimed at both engineers and architects building AI systems, as well as decision makers and business people who want to move beyond vector-search wrappers and design robust, context-aware foundations that enable reliable autonomous agents.

If you’re working on AI copilots, internal agents, or service automation systems and struggling with inconsistent data or fragile pipelines, this talk will provide a practical blueprint for architecting an intelligence layer that scales with organisational complexity.