Over the years, we’ve collected thousands of sources of electronically stored information, from “run-of-the-mill” file servers to the weird stuff like arcane, unix-based accounting systems. We built Culligo™ so that attorneys and in-house counsel could execute highly-targeted ESI collections and reduce their discovery spend.
Quantum’s rapid, intelligent Visual Discovery® workflow integrates and leverages AI, linguistics, text-based clustering and visual clustering technologies during early stages of the eDiscovery process.
The Proportionality Triangle is a discovery thought model used by litigators and in-house counsel to leverage the correlation between “just, speedy and inexpensive” in Rule 1 of the Federal Rules of Civil Procedure and the triple constraints of quality, time and cost in the project management triangle.
We’ve worked with e-mail in an eDiscovery context for a very long time. In general, we’ve found that the following data culling treatments (culling based on basic e-mail metadata, key terms & analytics) will reduce linear attorney review costs significantly.
The purpose of an e-discovery audit is to make specific data-driven recommendations on how organizations can reduce legal spend going forward by looking at overall discovery activity in the organization and examining how actual case data was handled using existing technology and processes. This page summarizes the purposes, methods, outputs, and reasonable expectations for Quantum’s e-discovery audits.