Beyond LLM Hallucinations: Grounding AI in Your Connected Enterprise Data

While generative AI has transformed how we interact with information, it hasn't yet delivered on its promise of revolutionising business intelligence.

"Where's my starship computer?"

It's a question many businesses are asking as they struggle to leverage AI, particularly LLMs, for meaningful insights on their own data.

The Problem with LLMs for Knowledge Retrieval

Large Language Models (LLMs) like ChatGPT are user-friendly and can provide quick access to general knowledge. However, they come with significant limitations:

Hallucinations
Limited Contextual Analysis
Lack of Explainability
Limited Proprietary Data Use

LLMs often generate plausible but incorrect answers due to inconsistencies in their training data. They also often miss relationships and insights that a human would recognize as obvious, and when applied to your own company data, LLMs struggle to retrieve accurate, relevant answers.

Can RAG Help?

Retrieval-Augmented Generation (RAG) emerged as a partial solution to these challenges. RAG is an AI technique that enhances text generation by retrieving relevant external information from a knowledge source to improve accuracy and context. By retrieving and grounding responses in factual, relevant data, RAG systems improve accuracy and reduce reliance on an LLM’s internal memory. This makes responses more reliable and better suited for business applications.

However, while standard RAG improves knowledge integration, it still has several fundamental shortcomings…

Poor Multi-Source Aggregation: They struggle with queries requiring integration across multiple data sources.
Over-Reliance on Vector Search: Statistical models alone miss deeper relationships in structured data.
Hidden Insights Remain Unseen: If insights weren't explicitly indexed, they won't be surfaced by the LLM.

A true AI assistant—one that understands your data like a starship computer—needs more than just clever text generation. It needs structure, relationships, and real-world grounding. That’s where GraphRAG changes the game.

GraphRAG: The Next Evolution of Grounded Retrieval

GraphRAG is the next evolution of Retrieval-Augmented Generation, combining the reasoning power of knowledge graphs with the flexibility of LLMs to deliver deeper, more accurate, and context-aware AI responses.

Deeper contextual understanding: Entities and their relationships provide a richer knowledge structure for the LLM.
Faster response times: Leveraging in-memory graph technology optimises retrieval speed.
Enhanced relevance: Structured entity-based retrieval improves answer precision.
Better regulatory control: More transparent, controlled, and auditable data handling

“GraphRAG systems capture rich semantic relationships that might be lost in a vectorized embedding” - Gartner

But Isn't Building A Graph Difficult?

Unfortunately, despite the advantages of GraphRAG, traditional approaches come with their own set of challenges, and they all revolve around building the Graph.

Slow Implementation: Data preparation and ontology design can take months.
Brittle Structures: Rigid graph schemas limit adaptability to evolving data.
Complex Integration: Businesses often need multiple tools to manage data, graphs, and AI interactions.

Get GraphRAG-Ready in Minutes with Conode

Conode has always eliminated the biggest hurdle to GraphRAG adoption: seamless knowledge graph creation. With Conode, you can build the Knowledge Graph you need for grounded GenAI in seconds.

100% No-Code ✅ Anyone can build a knowledge graph.
Automatic Data Fusion ✅ Conode automatically integrates diverse datasets for you, requiring no data prep.
Fast Embeddings ✅ Achieve10-100x faster embedding calculations compared to competitors.
Flexible, Scalable Architecture ✅ Conode's schema-free design ensures adaptability without rigid structures.

Coming Soon... Ask your Graph, Anything.

With dynamic Knowledge Graphs at your fingertips, you will be ready to ask any question across all your complex data.

We will shortly be announcing Conode's own GraphRAG agent Ask Your Graph—the future of AI-driven business intelligence. Ask Your Graph is a simplified interface which bridges the gap between the ease of use of ChatGPT, with benefits of a connected, grounded knowledge source.

Multi-source insights—not just keyword matches
Grounded, accurate responses with no hallucinations
Total data visibility and control—seamlessly switch between chat and graph
Context-aware answers tailored to your domain
Secure Role-Based Access Control

More coming soon, but here's a sneak peak 👀

Get In Touch

With Conode’s Ask Your Graph, the wait for a true starship computer is over. Natural, intelligent conversations with your data are finally here—grounded, explainable, and built for business.

Impatient? We're ready to speak to you. Reach out to info@conode.ai.