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New Macro Data Visualization Engine Powered by Reveal AI

Reveal, the global provider of the AI-powered eDiscovery platform, has announced the introduction of Streams, an entirely new way to uncover insights from today’s complex web of digital communications data sources using the power of Reveal AI.

After developing, what the company states is the most successful and widely-used data visualization tool globally, Reveal is raising the bar once again with Streams. Available early 2023, the macro-visualization engine maps massive amounts of data from traditional and alternative data sources to immediately uncover patterns saving time and resources, while exponentially amplifying insights. When Streams is used in concert with the full suite of Reveal AI-powered tools like the Cluster Wheel, Communication Map and AI Model Library, the results are unmatched in the industry.

“New communication platforms and formats have exploded in variety and adoption, creating a wealth of potentially relevant ESI sources that current discovery platforms struggle to parse,” said Wendell Jisa, founder & CEO of Reveal. “Streams solves this issue by bringing the varied threads together in a single, powerful interactive visual analytic tool that instantly becomes a force multiplier for case teams.”

What sets Streams apart is its ability to weave communication threads into a single AI-powered visualization that understands patterns, concepts and anomalies across multiple new and traditional communications sources including collaboration tools. Upon ingestion of data the visualization allows users to immediately layer insights into review, narrow or expand discovery and find actionable insights in minutes rather than weeks.

With the most adaptability and scalability of any tech solution on the market, the Reveal 11 AI platform is uniquely equipped to handle matters at any scale. Combined with the industry’s most advanced visualization tools on the market, clients can now quickly and more deeply understand their digital environments in ways traditional tools simply cannot replicate.

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