Smarsh Enterprise Archive Customers Can Leverage Brainspace Machine Learning to Find New Patterns in Complex Data, Reduce Time and Cost for E-Discovery
Smarsh, helping customers get ahead – and stay ahead – of the risk within their electronic communications, announced an integration with Brainspace, the world’s leading data analytics platform for investigations, e-discovery, and compliance, at Legalweek 2020.
Smarsh Enterprise Archive customers can now leverage Brainspace’s advanced data analytics and machine-learning engine across their archived electronic communications. This enables users to drill down into complex sets of messages and draw actionable insights for e-discovery, litigation and investigations.
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“Smarsh customers can harness Brainspace’s machine learning and natural-language processing to visualize their communications data, revealing hidden themes and relationships between various messages, terms and participants,” said Adam Miller-Howard, Vice President of Business Development for Smarsh. “In this way, in-house discovery teams can quickly uncover hidden patterns in their data to reduce the need for expensive e-discovery software and outside counsel.”
The Smarsh Connected Suite enables the capture, archiving, supervision and discovery of more than 80 communication channels behind a single pane of glass. Content is captured in its native format with full fidelity metadata, enabling users to review content in its full conversational context. Customers can both leverage the productivity benefits of the latest social, mobile and collaboration tools, and strengthen their compliance and e-discovery efforts.
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Brainspace applies machine learning capabilities to automatically organize archived data into interactive visual displays. The solution applies augmented intelligence to rapidly surface data insights while reducing false positives. Users can identify hidden patterns in their data, saving time and reducing their reliance on third-party case assessments.
“The combined power of Smarsh and Brainspace allows users to take full control of their data to greatly accelerate the eDiscovery process, enabling teams to work both smarter and faster,” said Miller-Howard.
In addition, Brainspace’s supervised machine learning enables users to train the machine to identify specific human behavior or intentions. Customers will be able to transmit data from Brainspace back to the Smarsh Enterprise Archive for retention, or to third-party review and production tools.
“Brainspace is excited to work with Smarsh to provide a next-generation solution for e-discovery analytics and archiving, across electronic communications,” said Barry Fields, Chief Revenue Officer for Brainspace. “Now users can really dig into their archived communications data to visualize unforeseen connections, improving their outcomes for litigation and investigations.”
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