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A little over ten years ago the adoption of what is commonly referred to as the "in/out" pricing model was born. In essence, service providers would charge a one-time per gigabyte rate for ingesting and indexing containerized source data (the "in"), apply search terms, then publish all remaining data to a review workspace. The volume of data that survived search term culling would carry another one-time per gigabyte processing charge (the "out"). Recent advancements in e-discovery software combined with new rules have rendered this pricing model, and disjointed workflow, obsolete. However, many buyers are still clinging to the status quo.
This presentation takes a 30,000-foot view at how and why the old pricing model came about, then presents a step-by-step guide through a real-world scenario leveraging the latest technology with a more streamlined approach. The end result is a data discovery lifecycle that provides greater transparency, reduces turnaround time, and minimizes opportunity for human error—all while reducing overall discovery spend.
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