AI Provider Selection

AutoCISO uses AI to extract user lists from access screenshots and PDFs, classify assets and suppliers, and prefill ISO control evidence. Two providers are supported:

• Anthropic Claude (default). Screenshots and PDFs are sent to Claude as images and read directly.
• DeepSeek. Images are converted to text by OCR inside AutoCISO before anything is sent out. Email addresses in that text are masked, and only the masked text goes to the provider — image bytes never leave AutoCISO.

Which provider your organisation uses is set for your AutoCISO deployment. Ask your account manager or support if you need it changed.

What changes per flow

Image-based asset and ISO certificate extraction always uses Claude, so Claude remains a sub-processor for your organisation even if you choose DeepSeek for everything else.

Personal data handling with DeepSeek

Before any text is sent, AutoCISO masks email addresses and replaces each with a placeholder that means nothing outside your request. The placeholders are restored in the result, so extracted rows still match your employees. The model never sees a real email address.

Names and phone numbers are not masked — only email addresses.

If you supply a custom prompt for an asset, the rules that handle these placeholders are always appended and cannot be removed.

Extraction accuracy when only text is sent

With DeepSeek, no model ever sees your screenshot — it reads the text that OCR recovered. That text carries predictable damage, and it is worth knowing what to expect:

• Characters are misread. Sergey Ilin is commonly recovered as Sergey lin (capital I read as lowercase l). Extraction is instructed to repair obvious character damage and keep the surname rather than drop it.
• Layout is flattened. Sidebars, headers and buttons interleave with table rows, and badges next to a name (Owner, Admin) arrive as stray characters. Extraction reads these as roles or ignores them, not as names.
• A damaged row is never “repaired” into a different person. An empty field is preferred over a plausible guess, and a row must appear in the source to be reported.

The email is what carries a match. Employee matching treats an exact email as decisive, so a row whose name arrived damaged still attributes correctly as long as its email survived. Where the name is ambiguous and no email was recovered — a row reading only Sergey when two employees share that first name — AutoCISO raises it for review rather than guessing. See Correct a misrecognised employee.

If accuracy matters more to you than keeping images inside AutoCISO, ask support to send audit screenshots to Claude as images. That sends image bytes to Anthropic — a deliberate trade of the text-only guarantee for extraction accuracy.

When to choose DeepSeek

Choose DeepSeek when:

• Your organisation requires that no screenshot or PDF image leaves the platform for audit ingest.
• You want lower cost on text-only flows such as chat and name or website classification.
• Your data-processing agreement covers DeepSeek as a sub-processor. Update your RoPA (Privacy Register) and Data Processors accordingly.

Remember that asset and ISO certificate image extraction still uses Claude either way.

What does NOT change

The console looks the same whichever provider you use, and the audit results you see are stored in the same structure. Personal-data tokenisation on your own inputs works as before, independent of the email masking described above.