How I Built a Data-Based Near Zero-Hallucination AI System @ai-science
How I Built a Data-Based Near Zero-Hallucination AI System  @ai-science
Uploaded May 2026 | Updated September 2026, 3 weeks ago
Join the next cohort and build something like what you see in this demo:
https://ai.science/products-services/llm-agents-bootcamp

What happens when you combine public government data, AI agents, and a system designed to eliminate hallucinations? In this demo, I showcase a trustworthy AI architecture built on top of CBS, the Dutch National Open Data Agency. The challenge was simple: massive amounts of reliable public data existed, but extracting meaningful insights with LLMs was slow, unreliable, and often filled with fabricated answers.

To solve this, I built a layered architecture combining an MCP server for verified data retrieval with specialized AI “skills” that enforce reasoning boundaries, source attribution, and domain expertise. The result is an AI system that can act like a real estate broker, journalist, analyst, or researcher while grounding every claim in authoritative CBS data.

Watch two live demos analyzing the same Amsterdam neighborhood through completely different expert lenses, all powered by the same trusted data layer. This project is a glimpse into the future of verifiable, explainable, and scalable AI systems.


#AI #ArtificialIntelligence #ClaudeAI #OpenData #MCP #MachineLearning #AITools #DataScience #LLM #TechInnovation #FutureTech #AgenticAI #TrustworthyAI #AIArchitecture #Analytics #Automation #RealEstateTech #Journalism #DataEngineering #AIProjects
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How I Built a Data-Based Near Zero-Hallucination AI System

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