Aparavi and Modus Forge Strategic Relationship to Reduce Data Risk, Data Costs & Complexity for Enterprise and Government Customers

Aparavi platform complements eDiscovery applications with data intelligence and automation for case assessments, investigations and legal discovery

Aparavi®, a catalyst in data intelligence and automation software, and Modus, a leading provider of eDiscovery and Information Governance services, today announced a strategic agreement to offer Modus clients, including law firms, corporations, and government entities, a Modus-branded edition of the Aparavi platform.

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“Enterprises of all sizes struggle under large unstructured data and are challenged to find, and identify the relevance, importance, and value of their information”

Modus has deployed Aparavi, The Platform, in a variety of environments to complement information security, compliance, retention, and eDiscovery and to reduce the cost and complexity of managing large unstructured data volumes. Aparavi, The Platform enables data discovery with automated classification, data optimization (including defensible deletion), and easy migration to alternative data stores such as on-premises storage or major clouds. It gives users visibility and insight into data, even across diverse systems and locations (core data center, cloud, edge and endpoint).

Aparavi users have found that 15-40% of data is Redundant, Obsolete, or Trivial (ROT), and intelligently removing this data streamlines the infrastructure – and reduces IT costs significantly. ROT data and dark data – whose contents and importance are unknown – also pose a risk that needs to be mitigated. Since an estimated 80% of enterprise data is unstructured, Aparavi’s platform uniquely slashes costs and risks. “The Aparavi Platform complements eDiscovery applications because its sophisticated search, index, and classification functions are ideal in early case assessment, investigations, and legal discovery. In areas of regulatory compliance, security, and protection, it delivers critical data insight that reduces risk and improves our customers’ ability to manage threats such as data leakage. Knowing what is relevant is critical to effective eDiscovery and Information Governance,” said Steven Horan, Modus Chairman and CEO.

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“Enterprises of all sizes struggle under large unstructured data and are challenged to find, and identify the relevance, importance, and value of their information,” said Adrian Knapp, Aparavi Founder and CEO. “With this strategic relationship Modus customers are now able to immediately reduce data risk, management costs, complexity, and reduce human error with automated data governance and compliance, even exploit their data for data analytics and machine learning.”

Aparavi’s platform complements eDiscovery software by radically speeding up managed review processes to find the most relevant data. An in-house team can curate documents before sending them to outside counsel for review, through powerful automation tools that discover, classify, optimize, and enable innovation while reducing human error. This eliminates potentially thousands or millions of dollars in processing, hosting, and review fees.

Aparavi helps meet information governance requirements with its comprehensive data intelligence and management that give a clear understanding of unstructured data from cradle to grave. It includes more than 140 predefined classifications that address regulatory compliance for vertical industries and countries and recognizes more than 800 patterns such as social security numbers or financial account numbers. It applies policies and triggers action based on information lifecycle, access requirement, content, risk level, regulatory status, and hundreds of other criteria. It also aids in data and IT consolidation by identifying and classifying critical data and redundant, obsolete, trivial data that can be removed, typically delivering 30% to 40% savings in data infrastructure.

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AparaviComplexityData CostsData RiskeDiscoveryEnterpriseGovernment CustomersModus ForgeStrategic Relationship
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