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Handling Slack Data in Discovery and Investigations

Slack Gears

Summary: Slack eDiscovery Tools

Slack data can be incredibly valuable, whether in litigation, compliance, or internal investigations. But without the proper tools, Slack data is virtually indecipherable.

  • Slack data exports as JSON files, which can be difficult or impossible to review.
  • The proper discovery tools can render Slack data into an easy-to-review format, surfacing valuable metadata, such as editing and deletion logs.
  • You don't need to pay exorbitant prices to handle Slack data; the right discovery platform will treat it just like any other project.

Making Sense of Slack Data

When you, or your client, exports data from a Slack workspace, it will come as several—potentially thousands—of JSON files, for Javascript Object Notation. And JSON data isn't something you can review like an email of PDF. Here for example, is what a simple record of a user joining a channel looks like when exported directly from Slack:

Slack JSON data for joining a channel

"Your engineers will know what to do with these," Slack explains.

But how many clients, and how many law firms, have engineers at all, let alone the engineering bandwidth to create a platform that can process and interpret Slack data? And when it comes to Slack review, very few legal tools are designed to handle Slack data.

As Slack data becomes increasingly rich and complex—full of information message type, edit logs, reactions and more—it becomes even more difficult to handle.

Take comments on a shared file, for example. In Slack, this would appear as a simple message under the file, just a few lines long. When exported from Slack, here's what that those comments look like when exported in JSON format:

Slack JSON data for comments on a shared file


A single line in Slack can make up hundreds of line of code when exported

You certainly can't review these files on their own. And you can’t toss this into just any discovery software and expect it to be reviewable.

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How to View Exported Slack Data:

Processing Slack Data

To make sense of data exported from Slack, you need a platform that is designed to process Slack's JSON data and render it in a form at that is easy to review. That doesn't mean just extracting text messages and leaving the rest behind. There is valuable information in Slack's deluge of JSON code, after all! Your platform should also make that information available—particularly information such as user names, time and date stamps, file types, comments, and edit or deletion records.

Instant discovery software like Logikcull can do just that, in a platform that is powerfully simple. In Logikcull, handling Slack data is as easy as upload, search, download.

Upload Search Download Slack Guide

Once your data is exported from Slack, it can quickly be uploaded to Logikcull. During the upload process, that data goes through 3,000 automated processing steps: text is rendered and indexed for the most accurate eDiscovery search available, metadata is extracted and preserved to protect against spoliation, quality control tags are applied, and much more.

Slack data is rendered instantly searchable, whether you’re looking for simple text search for keywords or constructing an advanced Power Search based on metadata fields. When it comes time to review Slack documents, Logikcull creates a representation of Slack data similar to how it is displayed in the Slack user interface.

See it in action below:

Smart Filters

Quickly narrow your documents

QC Tags

Drill into Slack data

Keyword Search

Quickly find edits and deletions

Tips for Reviewing Slack Data

Once exported from Slack and processed for review in a platform like Logikcull, many of the same discovery best practices that apply to any document review can be employed on Slack data. Customized tags can be created, search terms can be tested and refined, perhaps through a bulk keyword search, and documents can be batched out to your team for review.

You will also want to be able to quickly identify Slack documents from the rest of your document corpus. In Logikcull, when Slack dies are uploaded, each Slack document is marked with a Slack QC tag. By selecting the Slack QC tag, you can run searches against just Slack data, or filter your Slack documents by date range, custodian, keyword, or numerous other properties.

As Slack creates a near-constant stream of communication, it's likely that the vast majority of it will be unnecessary junk. Using powerful culling and search technology, reviewers can easily cull through the vast amounts of data produced by Slack to quickly find and tag the most important information—and cut out the rest.

When review is completed, those Slack documents can be downloaded and produced to others through a secure, permission-based link, allowing you to make sure that your data stays protected throughout your discovery process.

Finding Deleted or Edited Messages in Slack Metadata

Remember that Slack records more data than the user interface displays. Thus, when a message is deleted in Slack, it will simply disappear—at least, that's what it appears like to users. Similarly, when a message is edited, only the final, altered text is displayed, alongside the parenthetical "(edited)." But, with the proper Slack retention settings, that information can be logged, retained, and surfaced on review.

If a message is deleted, Logikcull displays the deleted information and the time of its attempted destruction. If it is edited, Logikcull shows the original message, the altered version, and the time of the change. That way, review teams can bring clarity to otherwise opaque information—information that could be key to the discovery and investigation processes.

Reviewing Slack Data for eDiscovery in Logikcull


Find deleted or edited messages in with just two clicks.

Taking Control of Slack Data

Though Slack presents significant challenges when it comes to litigation and investigations, with the right tools, legal professionals truly can treat Slack as a “searchable log of all conversation and knowledge.”

The first step is to integrate Slack into your regular discovery and investigations process. That means discussing Slack retention and information governance policies with clients. It means adding Slack data to your preservation letters, requests for production, and custodian interviews.

It means looking for indications that Slack might be at issue in a matter, such as the email notifications many users get when receiving a mention or direct message. (Search for the keyword “Slack” or the email address “no-reply@slack.com.”)

Most importantly, it means finding a platform that can help you make sense of Slack, one that supports robust document review, tagging, and collaboration, without requiring the intervention of a highly technical IT team—and doesn't charge extortionary prices for it.

After all, if your Slack discovery solution doesn’t provide comprehensive review, tagging, and collaboration features, then it’s not giving you the tools you need to handle Slack data.

If your Slack discovery process requires you to bring on computer technicians or to pay for a six-figure software setup, then it’s only adding to the problems Slack data creates; it’s not solving them.

That's why Logikcull lets you turn Slack data from a burden into an opportunity, making Slack discovery and investigations simple, secure, and straight-forward.

It's the closest thing legal teams can get to a searchable log of all content and knowledge.

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