Document analysis, summarization, and topic signal extraction all run on hardware we own, not a shared cloud AI endpoint — the document never becomes part of someone else's model logs.
The obvious shortcut, and its real problem
"Just paste it into ChatGPT" is the fastest way to summarize a pile of documents — and the obvious problem if those documents are client files, medical records, or anything under an NDA, since the text now sits in a third party's logs.
What the job returns
Each document is extracted, analyzed, and summarized, with entity signals and topic signals pulled out alongside the summary — all from a job that runs entirely on hardware we own.
Where this breaks down — said plainly
- Topic signals are frequency-ranked key terms, not deep semantic topic modeling. A real, useful signal — just not the same thing as a research-grade topic model.
- Summaries are a starting point, not a final read. For anything consequential, read the source document too.
Related guides
- Local AI vs. cloud AI for documents
- Is it safe to use AI on privileged documents?
- Pull text and tables out of PDFs without a cloud API
Where this fits on the site: this is the Private AI document analysis and summarization service under Private document analysis & summarization pricing — published tiers starting at $689 for up to 100 documents, no quote, no sales call. See Services & Pricing or go straight to Choose your job.