Consilio's CoreECI Cuts Document Review Costs by 95.5%
Discover how Consilio's Aurora CoreECI application transformed a complex eDiscovery process, achieving a remarkable 95.5% reduction in documents needing review and optimizing legal workflows.
Key Facts
- Consilio's CoreECI reduced document review by 95.5%, showcasing efficiency in eDiscovery workflows.
- Targeted promotion of 75,193 documents reveals cost-saving potential in legal review processes.
- AI performance improves with relevant data, indicating a competitive edge in legal tech solutions.
- Upstream decision-making shifts costs from review platforms, enhancing financial performance for clients.
- Flexible workflows allow adaptation to new data, signaling strategic agility in legal operations.
Summary
Summary
A highly regulated energy corporation faced challenges with managing a massive collection of over 1.6 million documents for legal review. By implementing Consilio's Aurora CoreECI, the company significantly narrowed the review set to just 75,193 documents, achieving a 95.5% reduction. This streamlined approach enhanced the efficiency of their review process and improved the effectiveness of their existing review platform.
Background
The customer is a highly regulated energy corporation that collected data from approximately 40 mobile devices and other sources. Prior to deploying the new solution, the company faced the daunting task of processing 1,670,964 documents, all of which would typically enter a review platform before any meaningful analysis could begin.
Challenge
The primary challenge was the inefficiency of the traditional review workflow, where all collected documents were sent to the review platform, leading to high costs and wasted resources. The legal team needed a way to filter out irrelevant documents before they entered the review process.
Solution
Consilio introduced Aurora CoreECI to the workflow, which allowed the project management team to apply 104 specific search terms and phrases to the entire collection. This process identified responsive documents and their families, promoting only the relevant subset to the review platform. The existing review platform remained in use, but the selection process was refined upstream.
Results
The implementation of Aurora CoreECI resulted in a dramatic reduction of documents promoted to review, from 1,670,964 to 75,193, marking a 95.5% decrease. This not only reduced the volume of material needing review but also optimized the use of the review platform's AI capabilities.
Key Insights
Business leaders should consider evaluating the criteria for document promotion before entering the review phase. By narrowing the focus upstream, organizations can enhance the efficiency of their review processes, reduce costs, and ensure that their review platforms operate on relevant data.
Customer Testimonial
No direct quote is available from the source material.
Entities Mentioned
Companies
Products
Technologies
Key Concepts
Definitions
- eDiscovery
- The process of identifying, collecting, and reviewing electronic data for legal cases.
- review platform
- A software system used to manage and analyze documents during the legal review process.
- AI assistants
- Artificial intelligence tools integrated into review platforms to help summarize and classify documents.
- document promotion
- The process of selecting specific documents for review based on predefined criteria.
- upstream decision making
- The practice of making decisions about data relevance before it enters the review process.
Use Cases
- →Reducing the number of documents for legal review
- →Improving efficiency in eDiscovery processes
- →Enhancing AI performance by narrowing the corpus
- →Applying specific search criteria before document review
- →Streamlining case management workflows
- →Facilitating better attorney decision-making
Frequently Asked Questions
What is the benefit of narrowing data before review?
Narrowing data before review significantly reduces the volume of documents that need to be processed, which can lower costs and improve efficiency. It allows legal teams to focus on relevant materials, enhancing the quality of the review.
How does Aurora CoreECI assist in the review process?
Aurora CoreECI helps determine which documents should be promoted to review by applying specific search terms and identifying responsive families. This targeted approach minimizes irrelevant data entering the review platform.
What role do AI assistants play in the review platform?
AI assistants in review platforms summarize and classify documents, making it easier for legal teams to manage large volumes of data. They perform better when working with a focused corpus of relevant documents.
What steps should be taken before data enters the review platform?
Before data enters the review platform, teams should process broadly, investigate early, promote selectively, and ensure that only documents meeting specific criteria are reviewed. This upstream decision-making enhances efficiency.
Can existing review platforms be used with new data evaluation methods?
Yes, existing review platforms can still be utilized while implementing new data evaluation methods. By narrowing the data upstream, teams can improve the effectiveness of their current systems without needing to change platforms.