What is the officially recommended workflow for enabling Atlas AI to reliably answer questions from uploaded PDF maintenance manuals

I uploaded a PDF maintenance manual into Cognite CDF using:

client.files.upload(...)

The document is successfully indexed by the Documents Engine.

I can confirm that:

- client.documents.retrieve_content() works
- client.documents.search() returns the document
- last_indexed_time is populated
- truncated_content contains extracted text

Example document metadata:

{
  "id": 3652062792350259,
  "external_id": "HACTL_CSS_Manual",
  "name": "HACTL_CSS_Manual",
  "title": "Hactl.md",
  "mime_type": "application/pdf",
  "last_indexed_time": "2026-05-06 14:57:28.531+00:00"
}

However, Atlas AI still responds with:

“I could not find any uploaded maintenance manuals related to wheel carriage troubleshooting in the system.”

Questions:

1. Does Atlas AI automatically use Documents Search semantic indexing from files uploaded with client.files.upload(), or does it require CogniteFile instances + upload_content()?

2. Is Atlas AI document retrieval based on:
   - Documents semantic search
   - passages/search
   - or instanceIds grounding only?

3. Could the issue be related to the document title metadata?
   Current title is:
   "Hactl.md"

4. Is there an official way to update the Documents title after indexing?

5. For Atlas AI grounding, what is the recommended ingestion architecture?
   - Files.upload()
   - upload_content(instance_id=...)
   - CogniteFile
   - Documents Search
   - or instanceIds?

6. What is the officially recommended workflow for enabling Atlas AI to reliably answer questions from uploaded PDF maintenance manuals?