AI developers are licensing internal records from established companies to train their models. Process manuals, help desk history, CRM notes, project archives, QA logs and team chat all qualify. It is a license, so you keep your data and keep using it. Interested in selling? See if your business fits the program in under a minute.
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Estimate the total written output of your business across every channel your team uses.
Most leaders can tell you their revenue to the dollar but have no idea how much their company has written. It is usually far more than they expect. This estimator adds up the text your team produces in five places: email, chat, documents, tickets and recorded meetings. Start with headcount and years in business. The daily habits are filled with typical office averages, so you can run it right away or adjust them to match your team. The result shows the total words written, how many printed pages that would fill, the size in AI tokens and the space it takes as plain text. A breakdown shows which channel produces the most. It is a helpful number for migrations, AI projects and any discussion about the value of your records.
| Source | Words per year | Total words | Share |
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Email and chat usually produce the largest volume because everyone uses them all day. Documents and tickets are smaller in volume but hold denser, more reusable knowledge. Both matter, for different reasons.
Plain text is tiny. A million words take about 6 MB. The files on your drives are much larger because of formatting, images and attachments, but the actual knowledge inside them compresses to a fraction of that.
Large archives become useful when they are searchable and organized. The same organization makes them attractive to AI developers, who pay established English speaking companies for licensed access to real business text.
Office workers commonly write somewhere between 1,500 and 3,000 words a day once email, chat and documents are combined. Roles in sales, support and management tend to be at the high end.
About 1.33 million tokens for normal English text. Token counts vary a little by AI model, but this ratio is the common rule of thumb for sizing datasets and estimating AI costs.
Around 2,000 single spaced pages at 500 words per page, or 4,000 double spaced pages. For comparison, a typical novel is 80,000 to 100,000 words.
Many teams now record and transcribe calls. People speak about 125 to 150 words a minute, so one hour of meetings produces roughly 7,500 words. That quickly becomes one of the largest text sources in a company.
Use it to plan storage and migrations, size an internal AI assistant, set expectations for a search project or judge whether your archive is big enough to interest AI companies that license business data.