Product Suite

Retrivika™ CM

Key functionalities include:

Case Management offers a comprehensive suite of features designed to streamline and enhance research and investigations.

Subject & Witness Management

Maintain detailed profiles of individuals involved in cases, track interactions, and link them to relevant evidence.

Evidence Management

Securely store, organize, and analyze digital and physical evidence, ensuring chain of custody and facilitating collaboration.

Case Project Management

Define case objectives, create timelines, assign tasks, and track progress with intuitive project management tools.

Case Forms & Workflow

Automate routine tasks, streamline data collection, and ensure consistency with customizable forms and workflows.

Team Communications

Keep team members informed and aligned with real-time task updates and secure in app communication channels.

Case & Evidence Auditing

Provide transparency and accountability with comprehensive audit trails documenting every action taken on a case or piece of evidence.

Case Packaging & Reporting

Generate professional case reports and seamlessly package case materials for presentation or transfer.

Webhook Integration

Seamlessly integrate with other systems and applications, enabling realtime data exchange and automated workflows.

Retrivika™ Search

Retrivika Search offers a robust set of features designed to empower efficient and thorough investigation.

Key features include:

Retrivika™ eDiscovery

Streamline your eDiscovery process with our comprehensive suite of tools.

Efficiently manage every phase, from identification and collection to review and production.

Reduce costs, ensure defensibility, and achieve successful outcomes.

Publications

Hyman, H. and Fridy, W. “Using Bag of Words (BOW) and Standard Deviations to Represent Expected Structures for Document Retrieval: A Way of Thinking That Leads to Method Choices.” NIST TREC 2010 Legal Track

Hyman, H. and Fridy, W. “Modeling Concept and Context to Improve Performance in eDiscovery.” NIST TREC 2011 Legal Track

Hyman, H, et al. “Using Recall and Elimination Terms in Separate Runs for High Volume Document Sorting.” International Journal of Machine Learning and Computing, Vol. 6, No. 2, April 2016

Hyman, H. and Fridy, W. “Using Exploration and Learning for Medical Records Search: An Experiment in Identifying Cohorts for Comparative Effectiveness Research.” NIST TREC 2012 Medical Track

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