Pangram raises $9 million to catch AI-written text and images before they fool you
A New York startup says its new detector is over 99% accurate at spotting AI-generated writing. Substack already uses it. Here is what that means for everyday readers.
Key points
- Pangram, a New York AI-detection startup, raised $9 million in funding led by Menlo Ventures in 2025.
- Its new text model, Pangram 4, claims over 99% accuracy at spotting AI-written or AI-assisted content.
- A new image-detection model, Pangram Image, is currently in research preview and will launch more widely in coming weeks.
- Substack has already built Pangram's technology into its platform so readers can see which newsletter authors use AI.
- A personal subscription costs $20 per month, and a free Chrome extension labels posts on X, LinkedIn and other sites in real time.
There is a lot of text on the internet that nobody actually wrote. AI tools have made it trivially easy to flood blogs, social feeds and even academic journals with content that looks human but was generated in seconds by a chatbot. Pangram, a two-year-old New York startup, thinks that is a problem worth solving, and investors just handed it $9 million to try.
The funding round, first reported by TechCrunch AI, was led by Menlo Ventures, with Haystack, ScOp, Script Capital and Cadenza also taking part.
What does Pangram actually do?
Pangram builds AI detectors: software that reads a piece of text or looks at an image and decides whether a human or a machine made it. The company launched two new products alongside the funding announcement.
The first is Pangram 4, its latest text-detection model. The second is Pangram Image, which scans photos and illustrations for telltale signs that an AI generated them rather than a camera capturing a real scene.
To train its text detector, Pangram fed the system tens of millions of known human documents. For each one, it then created a "synthetic mirror": a version covering the same topic, length and tone, but written by a frontier large language model (the kind of AI that powers ChatGPT or Claude). The system learned the subtle stylistic choices AI makes consistently, which lets it flag AI content without relying on hidden watermarks or copy-paste metadata.
The image detector works differently. It analyses pixel-level statistics: the fine-grained mathematical patterns that differ between a real photograph and an image a generative AI tool produced. Unlike the watermark checks used by OpenAI or Google DeepMind, which mostly spot their own output, Pangram Image is designed to catch AI images regardless of which tool made them.
Should you trust the accuracy claims?
Pangram says roughly one in 10,000 human documents gets incorrectly flagged as AI. That sounds reassuring, but no detector is perfect.
TechCrunch AI's reviewer tested the tool and found it correctly caught entirely AI-written articles from both ChatGPT and Claude, and was not easily fooled by light human editing of AI text. When the reviewer asked ChatGPT and Claude to polish one of their own human-written articles, Pangram scored it at 13% AI-assisted, which the reviewer considered roughly accurate. Occasional false positives did appear on individual sentences, particularly in dry, factual writing that can sound AI-like even when it is not.
For image detection, the tool correctly identified AI-generated imagery whether it was photorealistic or cartoonish. It even spotted an AI image placed inside a real photograph. One misclassification did occur during testing.
What does it cost, and who already uses it?
| Plan | Price | What you get |
|---|---|---|
| Web subscription | $20 per month | Full text and image detection on uploaded content |
| Chrome extension | Free | Real-time labels on posts across X, LinkedIn, Substack, Reddit and Medium |
| API access | Contact Pangram | Integration into your own platform or workflow |
Substack has already integrated Pangram's API so readers can see which authors write their newsletters using AI. Quora, schools, publishers and recruiters are among other API customers, according to co-founder Max Spero.
Why does this matter for ordinary readers?
The risks of unchecked AI content are real and varied. A Canadian politician accidentally read an AI prompt aloud during a parliamentary speech. Lawyers have cited fake legal cases that ChatGPT invented, leading to sanctions. The open-access research archive arXiv now bans authors for up to a year if submissions show clear signs that AI output was not reviewed before submission.
Pangram is not the only company chasing this problem. Winston AI, Originality.ai, Copyleaks and GPTZero are all building similar tools. But the funding and the Substack partnership give Pangram a meaningful foothold.
One privacy note worth knowing: when you paste text or upload an image to any cloud-based detection tool, that content leaves your device. Check Pangram's privacy policy before submitting anything sensitive.
Common questions
Does the Chrome extension cost anything?
The Chrome extension is free. It automatically labels posts on X, LinkedIn, Substack, Reddit and Medium as human or AI in real time, without you needing to paste anything into a separate tool.
Can it tell if a human wrote something and then used AI to tidy it up?
Yes, that is one of Pangram's specific goals. The system tries to flag different levels of AI involvement, from fully AI-generated text to content that was mostly human-written but lightly polished by a chatbot.
Will it flag my writing if I am just a clear, plain writer?
Possibly, in isolated sentences. The reviewer found that dry, factual writing occasionally triggered false positives. Running a full document through the tool is more reliable than checking individual paragraphs.
