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Nuix Enterprise Collection Center
Data collection tool for eDiscovery, investigations, and forensics

Nuix Enterprise Collection Center
Data collection tool for eDiscovery, investigations, and forensics
Nuix Enterprise Collection Center Description
Nuix Enterprise Collection Center is a data collection platform designed for eDiscovery, investigations, and digital forensics workflows. The tool enables organizations to collect data from multiple sources including laptops, desktops, enterprise file shares, and Microsoft SharePoint sites. The platform provides remote preview capabilities of target file systems before collection, allowing users to pre-filter data by document type, custodian, and timeframe. This filtering approach aims to reduce the volume of irrelevant data collected during investigations and legal discovery processes. The tool includes automation features for repetitive collection tasks, with support for scheduled recurring collections and multi-job sequences. Users can configure email alerts, reports, and logs to track collection status and progress. Enterprise Collection Center integrates with the broader Nuix platform for downstream processing, analysis, and production workflows. The system is designed to handle data collection requirements for legal discovery, internal investigations, compliance matters, and forensic examinations. The platform supports both connected and remote device collections, enabling data gathering from distributed endpoints and centralized storage systems. Organizations use the tool to manage collection workflows across multiple custodians and data sources while maintaining audit trails of collection activities.
Nuix Enterprise Collection Center FAQ
Common questions about Nuix Enterprise Collection Center including features, pricing, alternatives, and user reviews.
Nuix Enterprise Collection Center is Data collection tool for eDiscovery, investigations, and forensics developed by Nuix. It is a Security Operations solution designed to help security teams with Automation, Compliance, Data Analysis.
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