Client Overview
An AM LAW 200 Law Firm engaged StreemView to analyze a Slack data population comprising over 700k messages across 5,400 distinct conversations and channels. The goal was to apply negotiated Boolean search terms in a defensible, efficient manner to identify responsive evidentiary content without overrunning downstream review processes.
Challenge
The client needed to balance defensibility with efficiency in their Slack data review. They needed to apply negotiated search terms within a court-mandated ±10-message context window in a data population of nearly three-quarters of a million messages scattered across thousands of channels—a significant data volume that could otherwise have meant significant costs eDiscovery workflows and review. To apply basic Boolean or proximity searches against legacy 24-hour RSMF data would result in significant misses in evidentiary content given the inability for terms to identify relevant messages when terms fell on different calendar days, even if only minutes or hours apart.
Solution
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End-to-End Ingestion
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Loaded >700k messages into StreemView platform within hours.
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Hit Window Proximity Search
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Configured StreemView’s patent-pending Hit Window to capture term hits occurring within a 30-day rolling proximity, ensuring logical connections aren’t lost by 24-hour boundaries.
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Contextual Expansion
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Applied an ESI-protocol requirement to include ±10 messages around each direct hit, preserving context and conversation flow for review and production.
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Selective Export
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Enabled the ability to promote only the relevant messages and attachments in RSMF—rather than the entirety of the population—for downstream production review.
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Results
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Direct Hits Identified
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StreemView: 1,206 hits in 41 conversations
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Traditional 24 Hr RSMF Approach: 192 hits in 33 conversations
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Total Messages & Attachments Exported (±10 Context)
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StreemView: 10,563 items, resulting in a >99% reduction compared to data ingested
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Traditional 24 Hr RSMF Approach: 2,012 items
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Relevant Message Yield Improvement
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500% more direct hits with StreemView
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81% of relevant content by message volume (76% by RSMF count) missed by traditional 24 Hr RSMF approach, but successfully identified by StreemView
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20% of distinct conversations with hits were missed by traditional 24 Hr RSMF approach, but identified by StreemView, helping avoid lost knowledge of who participated in relevant conversations
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Precision Gain by Limiting Hit Window
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Eliminated 13,467 peripheral items that fell outside the 30-day window
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Improved result-set precision by 56%
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Conclusion
This matter vividly demonstrates that StreemView’s conversation-based search and Hit Window approach are the only safe and accurate methods for applying Boolean terms to modern text message and chat data. By breaking free of rigid 24-hour segmentation and surgically promoting only the content that matters—augmented with context windows—legal teams can dramatically boost hit rates, reduce review volumes, and control costs without compromising defensibility.
