Introduction
Auto Tags in Logikcull provide alerts on important metadata and processing details, such as potentially privileged emails, duplicates, and more. These tags help users to better understand their data and streamline the review process.
How does it work?
How does it work?
Auto Tags (QC Tags) tell you things like:
How many potentially privileged emails were detected?
How many documents were from a database upload?
How many documents have a duplicate?
...and more.
What if a person was sending privileged emails with PDF attachments to a law firm that the attachments themselves contained embedded images or screenshots, like photos or scanned documents? Would you want to have the option to review just those files?
With Logikcull, you can. (Hint: filter on the "Has Deep Text" Auto Tag.) This is just one example out of thousands where you can leverage Auto Tags to uncover more information about your data.
Locating Auto Tags in your Project
Locating Auto Tags in your Project
Auto Tags are automatically applied during post-processing, and appear in three locations in your Logikcull Project: the Filter Carousel, Search Results, and the Document Viewer.
If you're curious what an Auto Tag means, simply hover over its name and the tooltip box will tell you.
Auto Tags in the Filter Carousel
Auto Tags in Search Results
Auto Tags in Document Viewer
Auto Tags with Descriptions
ℹ️ Auto Tags with an * next to their name indicate Subscription Only features.
Auto Tag | Description |
Embedded Document | Documents that are not email attachments, but have come from within another document. E.g., a .PPT within a .DOC is an embedded document |
Failed Extraction | Containers that failed to explode any files |
From Box | Documents that have been imported from Box |
From Import | Documents imported from a database (i.e. production, load file, etc.) |
From Slack | Documents that are part of a Slack archive |
Has BCC | Emails that contain BCC (Blind Carbon Copy) metadata |
Has Deep Text | PDFs with additional searchable text that is found after running DTR (Deep Text Recognition). This indicates that the PDF has an embedded image that contains text. |
Has Duplicate | Documents that are duplicates of other documents |
Has Embedded Files
| Documents that are not email, but contain embedded files as attachments. For instance, a .DOC that contains an embedded .PPT file |
Has Hidden Comments | MS Excel documents containing hidden comments OR PDFs containing comments or “sticky notes" ℹ️ Please note, Logikcull does not render hidden comments in the document viewer. Depending on whether the document was uploaded with a text layer that notes the comments, Hidden Comments may be viewable in the Text View. |
Has Hidden Worksheets | Documents that contain MS Excel hidden worksheets.
ℹ️ Please note, Logikcull will attempt to render hidden worksheets in the document viewer. |
Has MS Office Macros | Documents that contain MS Office embedded macros |
Has No Native | Imported documents that have no Native File |
Has No Text | Documents without any extracted or OCRed text |
Has Revisions | Documents that contain MS Word revisions or document comments |
Has Speaker Notes | Documents that contain MS PowerPoint speaker notes |
Has Threads | Documents that are part of an Email thread |
Has Virus | Documents that have been detected to contain a virus. These documents are quarantined during processing and can not be downloaded |
Is a Copy | This document is a copy of a document from another project |
Is Overlaid | Overlay(s) applied to document |
Edited Metadata | The file name for this document has been manually edited via the "Edit Metadata / File Name" option |
Last Email | Email that is the last message of an email thread or is a message without a thread. When part of a thread, this tag indicates the end of a particular thread and not the inclusiveness of the thread's contents within this email.
ℹ️ More information on this tag can be found in THIS ARTICLE. |
Mismatched Extension | Documents with incorrect or missing file extensions. E.g. a .DOC file that is actually a .PPT file but with an incorrect extension in the filename metadata |
Nist File | Documents identified as being part of the NSRL database of known computer files |
None | Use this Auto Tag to find documents that contain zero Auto Tags |
Not Rendered | Documents that were not rendered to PDF during processing |
Ocr Failed | Document where OCR (Optical Character Recognition) was attempted but failed |
Ocred | Documents that were OCRed (Optical Character Recognition) so they can be searched. |
Potentially Privileged | Emails that have a law firm email address in the From, To, CC, or BCC fields. They are considered to be potentially privileged. Suggest a new domain name by clicking the Get Support link in your Account drop down menu at the top of the screen. |
Protected | Documents that are password protected |
Rendered Text | The document's text was used to render the document to PDF. This happens if all other means to render the document fail |
Transfer Failed | The transfer of this file from Box failed or was corrupted |
Truncated Email Metadata | Documents whose To, CC, or BCC fields exceed system capacity for indexing |
Truncated Text | Documents whose text length exceeds system capacity for indexing |
Was Copied | This document was copied to another project |
Zero Bytes | Documents that have a file size of zero bytes. These documents contain no content. |
From Google Vault* | Documents imported from Google Vault |
From MS365* | Documents imported from MS365 |
Has Slack Deleted Messages* | Includes messages that were deleted in Slack |
Has Slack Edited Messages* | Includes messages that were edited in Slack |
Has Splits | PDF documents that have been split into smaller PDF files. |
Inclusive Email* | Emails that include all unique content of a thread. |
Is Slack 1:1 DM* | Is Slack 1:1 Direct Message between two parties |
Is Slack Multi-Party DM* | Is Slack Multi-Party Direct Messages |
Is Slack Thread* | Is Slack Thread |
Rendered From Import | Imported documents that have been rendered from native |
Split From PDF | Documents that were created by splitting a large PDF into smaller PDF files. |
Transcribed | Audio content was transcribed and is text-searchable |
Transcription Failed | We were unable to transcribe audio content. This file is not text-searchable. |
PII Detected | Personal Identity Information (PII) is detected with a 75% or greater confidence level |
PII Detection Failed | PII Detection Failed in the Document |
PII Detection Skipped | PII Detection was skipped |