Every answer is grounded in millions of Wikipedia articles, so you get reliable information instead of confident-sounding nonsense.
The Hallucination Problem
AI models don't actually "know" things—they predict what words should come next. This makes them fluent, but not always accurate. When they don't have the answer, they don't admit it. They guess. And those guesses often sound completely real.
Cloud AI can search the web to ground answers in facts. Offline AI usually can't. Without a knowledge source to check against, you get an AI that confidently answers questions.
How ColdNet Solves This
ColdNet uses a technology called RAG—Retrieval-Augmented Generation. Instead of letting the AI guess at answers, ColdNet first searches through a built-in knowledge base of Wikipedia articles to find relevant, verified information. Only then does the AI generate a response, grounded in actual facts.
How ColdNet retrieves and grounds answers in verified knowledge.
The result: answers backed by one of the world's largest encyclopaedias, not confident-sounding guesses.
The Difference in Practice
Cloud AI
Who invented the telephone?
ColdNet
Who invented the telephone?
When the AI Doesn't Know
What happens when you ask about something not in the knowledge base? Unlike other AI that will confidently fabricate an answer, ColdNet's RAG system recognises when it lacks relevant information. The AI will acknowledge the limits of its knowledge rather than making something up.
This might mean ColdNet occasionally says "I don't have detailed information about that specific topic" rather than spinning an elaborate but fictional response. We consider that a feature, not a limitation. Knowing what you don't know is more valuable than false confidence.
Accuracy Comparison
How different AI approaches compare on reliability and accuracy.
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