Efficient eDiscovery for massive collaboration datasets

The process of identifying, preserving, and analyzing electronic data to respond to legal or regulatory requests is known as eDiscovery. When required for litigation or investigation, electronically stored information (ESI) must be captured in a format that is defensible and searchable. This data can come from emails, instant messages, social media posts, business documents and more. Because of the volume of data involved in ESI, eDiscovery can be extremely costly to organizations that don’t have solutions in place to make their data accessible. 

eDiscovery within collaboration tool datasets is possible, but it can be incredibly complex, making it a slow and expensive process. Legacy eDiscovery tools were built for business communications with formal structures, such as emails. Collaboration messages lack this structure and don’t always record who has access to what data — for example, all users can view messages in public channels, even if they are not channel members.  

Collaboration tools enable a range of features that makes eDiscovery more complicated to perform. For example, collaboration messages can occur in public and private groups or direct messages. This hinders an investigator’s ability to search chat history because a user may have posted in locations that are not readily visible. To search collaboration messages effectively usually requires the use of a third-party tool. However, if that tool does not capture in real time a complete record of all revisions and deletions, spoilation is easy because custodians can always edit or remove their messages. 

Early case assessment (ECA) is an eDiscovery process that helps legal teams make informed decisions about how to approach a case by identifying key information to understand the scope and merits of a case and estimate potential costs. ECA can also help legal teams identify potential risks and opportunities, such as data privacy or regulatory compliance issues, and develop strategies to mitigate those risks. To approach early case assessment efficiently, investigators must be able to search collaboration messages and surface all relevant content and context. This requires permissions to search all messages, including private and direct messages. Full administrator privileges and/or a third-party eDiscovery platform that plugs into the collaboration tools are typically required to enable early case assessment in collaboration. 

Aware enables investigators to conduct any kind of eDiscovery investigation with federated search for collaboration messages from a centralized archive that contains a complete record of revisions and deletions, captured in real time. 

Aware exports eDiscovery and early case assessment results to .dat and .csv formats along with .txt files of every message and text base file. These exports are compatible with all major eDiscovery software, enabling legal teams to analyze collaboration search results according to their usual workflows. 

Aware ingests collaboration messages from all major tools across the enterprise environment, then normalizes and infuses the data with AI/ML metadata insights designed for the nuances of collaboration. This ensures no loss of context and a complete, defensible record of all messages, including revisions and deletions. From the Aware platform, investigators can conduct federated search of collaboration messages within all tools simultaneously. Searches may be initiated by a range of variables, including custodian, location, message type, date and time, and other factors. Results can then be narrowed by enhanced insights such as sentiment or toxicity. This reduces the time to discovery by producing the most relevant results, delivered with complete context for better understand of who, what, where, when, how, and why.  

Performing eDiscovery in collaboration presents several challenges. Varying permissions regarding message visibility make it harder to surface a complete record of all chat messages. Custodians retain control of their messages after sending, meaning they can edit or delete what they wrote, even months afterward. This increases the likelihood of spoilation. And legacy eDiscovery tools cannot process non-standard message features such as emojis and gifs, leading to missing context. Aware solves for all these problems by ingesting collaboration messages in real time into a centralized archive built for the nuances of collaboration data. This reduces time to discovery and empowers faster eDiscovery search by producing only the most relevant results, without loss of context. 

By retaining a complete, normalized, defensible record of collaboration messages, Aware supports a range of regulatory and policy needs to manage and control collaboration data. Additionally, Aware’s intelligent metadata supports the extraction of powerful insights from collaboration messages at scale. Some of the primary reasons major enterprises use Aware for collaboration data include: data loss prevention (DLP), insider risk detection, forensics and investigations, compliance adherence, information governance, employee experience, toxicity detection, business feedback loops and key initiative tracking.