Superior technology, and the talent to use it.
Strategic’s eDiscovery Services provide an alternative to the traditional process and review workflow. There is no per-gigabyte data ingestion or migration fee when using the Strategic eDiscovery Cloud. The Strategic intelligent review workflow and cost structure incorporates the expertise of the Strategic eDiscovery support team with Relativity’s technology-rich review platform to increase the efficiency of the document review while reducing the review time and cost.
Strategic eDiscovery Cloud Environment–Infrastructure
Design and Security
The Strategic eDiscovery Cloud environment is hosted at Equinix, one of the premiere co-location facilities in the country. Equinix meets the highest security standards (SSAE16 SOC-1 Type II Certified) and boasts 99.9999% uptime for all systems including power and HVAC. The Strategic eDiscovery Cloud environment is resilient, with redundant power supplies. At the network level, we are a Cisco shop with redundant hardware for all firewalls, routers and switches. All hardware is configured for automatic fail-over. We follow best practices as defined by Cisco for security. The server farm is virtual, with multiple instances of each application running for redundancy.
kCura Relativity Review Platform
Each Relativity database is tailored with customized fields, views, and layouts that meet the unique needs of every case. In addition to customizable templates and a wide variety of flexible tagging, highlight, redaction and reporting options, Relativity has the power of advanced analytics to enhance review workflows to deliver results quickly and accurately. The Strategic eDiscovery team provides complimentary one-hour online user training for Relativity at the beginning of each case, and additional training is available upon request.
Relativity structural and conceptual analytics, including Relativity assisted review (predictive coding), play a pivotal role in the development of the Strategic eDiscovery intelligent review workflow. Combining the consultative expertise of the Strategic eDiscovery support team and Relativity technology results in a superior review workflow customization unparalleled in the industry.
Relativity Structural Analytics
Relativity structural analytics better prepare your documents for review.
- Email threading organizes emails that were part of a single conversation and identifies the inclusive documents within a thread. Batching only the inclusive or end e-mail in preparation for the 1st pass review will reduce the number of documents for review by 25% or more.
- Near-duplicate detection can assist the reviewer with quickly finding documents with highly similar content.
- Foreign language identification can batch documents by language or in preparation for predictive coding.
Relativity Conceptual Analytics
Relativity conceptual analytics improve review efficiency and enhance quality control.
- Clustering provides a high-level overview of the topics found in each matter.
- Concept searching allows the reviewer to submit relevant documents or passages of text to the analytics engine to identify conceptually similar documents within the collection, thereby significantly reducing review time. Documents can be sorted into related batches without user input.
- Repeat content identification (e.g., e-mail footers) is automatically identified and can be filtered out of the data set.
- Predictive coding utilizes Relativity Assisted Review, an analytics component of Relativity. Predictive coding prioritizes documents so the most relevant are reviewed earlier; it also typically reduces document volume.
Relativity Assisted Review
There are several parameters for determining whether a project is suitable for predictive coding, including the type of matter, its risk profile, the availability of outside counsel, the timeline, and the document volume and richness. We have significant expertise in the evaluation of the suitability of predictive coding for an assignment and the implementation of the processes thereof, if appropriate.
Our predictive coding processes and workflows are collaborative and transparent, and we provide extensive reporting throughout to ensure that legal analysis and judgment is based upon all available information, and that the entire process is defensible.
Predictive Coding Workflow
- Attorneys with substantive knowledge of the matter create a “test” set of documents, used to inform the predictive coding engine on the baseline of responsiveness.
- The attorneys code “seed sets” on an iterative basis to further teach the predictive coding engine the meaning of responsiveness.
- The iterative process is repeated until “stability” is achieved; subsequently, the decisions incorporated in the seed set are technically replicated through the balance of the document population.
The output of the predictive coding engine is the ordering of documents from most responsive to least responsive. Then the project team conducts issue coding, beginning with the documents receiving the highest responsiveness score. At several points, the team identifies the richness (percentage of responsive documents) and precision (percentage of correctly coded documents) to determine when to cease the full review and begin sampling of the remaining documents.