What are AI Hallucinations?

We’ve all been there. You ask your AI assistant a simple question—maybe about a company policy—and it confidently gives you an answer. It sounds right. It uses all the right words. It even cites a document.

But then you check, and it’s completely wrong.

Welcome to the world of AI hallucinations, where your assistant fills in the blanks with its best guess, even when the truth isn’t there.

Sometimes it’s harmless. Other times it can lead to real problems. For example, giving customers bad information, approving the wrong terms, or misinterpreting policies.

So, why does this happen? And more importantly, how can you stop it?

Why Does AI Make Stuff Up?

AI hallucinations happen when a language model doesn’t have the facts it needs but it answers anyway.

It’s not lying. Actually, it’s doing what it’s built to do: generate plausible-sounding text based on patterns.  Remember, AI doesn’t “know” anything. It’s just generating the most probable response to a question (prompt).

Adding curated resources to your AI helps mitigate problems by letting your assistant pull from your internal documents, policies, databases, and more.

But even this method can fail if the data it’s searching for is messy, incomplete, or outdated.

Here’s what often goes wrong behind the scenes:

• AI can’t find the correct document, so it guesses.
• AI pulls from the wrong version of a policy.
• AI gets confused by bad OCR text from poorly scanned documents.
• AI retrieves part of a document but misses the key details.
• AI grabs HTML junk, like a footer or a sidebar. And AI then thinks that data is important.

The bottom line? If your assistant is searching among poor data, you’ll get poor answers.

Curating Your Data: The Secret to Smarter AI

Think of your AI assistant like a chef.  

If you give it fresh, quality ingredients, it’ll make a great meal. If you give it expired milk and wilted lettuce, it’s going to serve you a disaster.

Curating your data is giving your AI the best ingredients possible.

Here’s what that looks like in practice:

• Clean up the junk: Get rid of duplicates, outdated versions, and OCR errors.
• Chunk your content: Break big documents into smaller, meaningful sections so your AI can grab precisely what it needs.
• Connect the good stuff: Hook up databases and real-time data from web services so your assistant can find accurate, current information when it needs it.
• Strip the noise: Remove HTML clutter, footers, and random legal disclaimers. clean it up before your AI gets confused by it.
• Add helpful context: Metadata like dates and other fields help your AI find the most relevant data every time.

Curating your data means more accurate answers and a whole lot less second-guessing.

Why Data Curation Matters More Than Ever

Resourced-based AI assistants are changing how we find and use information at work.  But if the data isn’t correct, the assistant won’t be right, no matter how cutting-edge the model is.

Taking the time to prepare your data makes the difference between an AI you can trust and one you constantly have to fact-check. This is true for electronic documents, scanned images, databases, or web content.

The good news is that Grooper was built to curate data!  

All of the methods we’ve brought to market to get good data from your documents are what you can use to “curate” your data for AI. And we’ve added new features that allow you to clean up HTML and XML data as well.  

So regardless of your source, Grooper can make your data AI-ready and give you the most accurate AI Assistants.

The future of AI is exciting. But only if you can trust the answers.  

Curate your data.

Trust your assistant so your users will trust the answers.