AI Fact Checker

You have a paragraph you are not sure about. Maybe it is a few lines from a draft blog post, maybe it is a claim you found on some site and want to trust. The AI fact checker sits right above this text.

Here is the routine:

1. Paste the text you want checked. Drop it into the text box as it is. The tool pulls out each checkable claim it can find in it.
2. Add context if the text needs it. This box is optional. A short note about the topic or the date the text refers to gives the tool something to judge each claim against.
3. Run it and read the verdict on each claim. Every claim comes back with its own result. Anything the tool cannot confirm gets marked unverifiable instead of getting a guess.
4. Open the sources for anything important. The tool points at evidence, but you are the one who decides whether a claim holds up.

That is the whole workflow. What it actually does with your text once you hit run is worth understanding too.

What the AI Fact Checker Does With Your Text

Once you hit run, the tool works through your text in two passes. Here is what each one does.

It splits your text into claims

First, it pulls out every checkable claim in what you pasted. A claim is a statement that can be shown true or false with evidence. A date. A number. A named event. A statement about who did what and when.

Opinions and style are not claims. Take a paragraph like this: “Our company was founded in 2019. Revenue grew 40% last year. We make the best coffee in town.” Only the first two sentences are checkable. The third is a sales line, and no search can settle it, so the tool leaves it alone.

It searches the web for each one

Next, it looks for evidence on each claim it pulled out, then gives every claim its own verdict. You get one result per claim, not one grade for the whole paragraph. That way a single shaky sentence does not spoil the rest.

Some claims come back marked unverifiable. That is not the tool failing. It means it found no solid evidence either way, and saying so beats a made-up answer. Treat it as a flag to dig into yourself, not as a pass.

Why AI-Written Text Needs a Second Look

That unverifiable flag matters more than it looks. Polished AI text can read like a finished fact and still be wrong.

A study by Forum AI showed how that plays out. Researchers put more than 3,100 news questions to four major chatbots. Nearly 36% of the election answers came back with at least one factual error.

What the researchers said next is the part worth sitting with. The answers that looked the most professional, with the strongest-looking citations, were the most likely to bury errors inside them. Clean writing and a tidy list of links are not proof of accuracy. They are just packaging.

Which is why a student essay or a marketing post drafted with a chatbot can look done and still carry a wrong number or an invented date. Catching that is a different skill from spotting AI writing at all. If you need that one too, here is how to detect AI-generated content.

One caveat on the figure. Forum AI graded the answers with its own model, so treat this as one data point, not a settled measurement.

How to Check the Sources Behind a Verdict

So you have a verdict on each claim, and each one points at a source. The last call is still yours. Only 42% of chatbot news users say they always or often click through to the original source, according to the Reuters Institute Digital News Report 2026. The other 58% click through less often.

Open the source and find the claim

Click the source listed next to a claim, then scan the page for that exact sentence, number or date. A page that talks about the topic but never states the claim does not back it up. If the words are not there, the verdict needs more checking.

Check the date, the author and who is behind the page

Then look at who published it and when. A study posted by the people who ran it beats a blog that quoted it secondhand. Same logic with an official page over a write-up of that page.

This matters most with numbers. Say a draft says a market is worth $12 billion and links to a marketing blog. Open the blog, find where the figure came from, and follow it back to the original report. The report may show a different number, a different year or a narrower scope. The repost is a pointer. The report is the proof.

Handle unverifiable claims

For a claim marked unverifiable, hunt for a primary source yourself: the company filing, the study, the official statistics page. Find one and you can keep the claim. Find none and you should cut it, or rewrite it to say only what you can show.

Want to see which tools work this way before you settle on one? Here is our comparison of AI fact checking tools.

Where the Tool Can Be Wrong

One warning deserves its own space. This AI fact checker is a first pass, not a final authority. Every verdict comes from the sources it managed to find. When the search turns up thin coverage, the result reflects that gap.

Think about a claim about something that happened last week. Few outlets have covered it yet, so the tool may mark it unverifiable even if it is true. On older, well-covered claims, a wrong source can push a verdict the wrong way. Errors happen in both directions.

Context you add can shift things too. If a date or topic note in the optional box is off, the claims get judged against the wrong picture. Check what you typed before trusting what comes back.

And when a result looks wrong to you? Trust that instinct. Open the sources, find a primary one yourself, and make the call there.

Who Gets the Most Out of It

Anyone pasting text into the box has a reason. But three groups tend to get the most out of a routine like this, and each one runs it at a different moment.

Writers

Check a freelance article or blog draft before it reaches your editor. You fix the shaky number yourself, so the editor spends their time on the writing instead of the facts.

Students

Run an essay through the tool before you cite anything in it. A claim that comes back unverifiable needs a primary source you can name, or it should come out.

Marketers

Check the stats in a landing page or product launch post before it goes live. One wrong figure in a public claim is the kind of thing that costs you trust later. And if this sits in a wider kit, here is our pick of tools for content creators.

Final Thoughts

Paste your text, read the verdict on each claim, then open the sources before you trust any of them. That is the whole routine.

And treat unverifiable as a starting point, not an answer. It means you have more digging to do. Doing that yourself is the part that keeps your work honest.

So run the checker on the draft you have open right now. Then go verify the claims that matter.