Questions and Answers
Do I need DEVONthink on the Mac too?
DEVONthink To Go can be used as a standalone application and we have many people using it on its own. However, due to iOS and mobile devices’ limitations, it doesn’t have all the same features and capabilities as DEVONthink on a Mac. It’s a functional application on its own, but it’s even more powerful when used together with our desktop application.
How safe is my data on my iOS device?
Data stored on your device is encrypted using iOS’ own encryption. So your databases are always encrypted and can only be read by DEVONthink To Go after you unlocked your device after a restart.
An additional app-wide passcode secures access to your data. Alternatively you can use Face ID or Touch ID.
What data is available in Spotlight?
Spotlight receives the name, the first 16 KB of text content, the comment, and the tags for each item as well as metadata like the item’s type, its icon, and the creation and modification dates.
16 KB seems to be the internal limit of Spotlight (as of today).
What if Spotlight shows no results?
Check DEVONthink To Go’s settings in the Settings app and make sure that Search & Siri Suggestions is switched on. Check also DEVONthink To Go’s own settings and switch on Spotlight if necessary. Then try to search for terms that you know that occur in the document, e.g. in its title. If still no results show up rebuild the Spotlight index (see the build-in documentation, chapter Appendix).
Why can't I sync via USB?
For a long time the USB port in iOS devices wasn’t available to third-party apps. We believe that synchronizing via the local network provides a fast and reliable method even for larger data sets.
Why is there no A.I. in DEVONthink To Go?
Like the human brain our artificial intelligence (AI) technology is based on connections between all objects. For this to work all these connections must be available at all times which requires a certain amount of memory (RAM).
Unfortunately, iOS does not use virtual memory and quits apps frequently when they use too much RAM. Therefore our technology can’t be easily ported to iOS and ARM processors at the moment.