Discover what is a load file in eDiscovery, its types, uses, advancements in platforms and associated cost savings.
How Leading eDiscovery Platforms Are Adjusting to Growing Demand
In recent years, eDiscovery has come to involve ever-increasing amounts of complex data. Many eDiscovery platforms are ...
In recent years, eDiscovery has come to involve ever-increasing amounts of complex data. Many eDiscovery platforms are adjusting to these challenges and growing demand by scaling capacity for ingesting, extracting, filtering and indexing more types of data.
- The eDiscovery industry is evolving to accommodate the increasing amounts of complex data and growing demand by scaling up capacity, processing throughput, automation, and AI/ML functionality.
- The use of cloud-based eDiscovery tools, data storage, and operations can be more readily scalable than conventional on-premises approaches to managing electronically stored information.
- Cloudficient offers enterprise legal departments and large firms next-generation cloud migration solutions that facilitate processing ever-increasing amounts of data on eDiscovery platforms, providing affordable, scalable, fast, and seamless cloud migration and onboarding services.
The leading service providers are also making advances in automation, artificial intelligence, machine learning and processing throughput. Find out how the top platforms in this sector are evolving to accommodate the proliferation of modern data types and deliver end-to-end eDiscovery solutions.
Increased Capacity on eDiscovery Platforms
A growing base of customers with expanding data demands is driving companies that offer eDiscovery tools to expand the capacity of these resources. The premier platforms are taking a multi-pronged approach to optimize performance during ingestion and indexing to help customers manage growing volumes of complex data.
The most competitive eDiscovery platforms are scaling up their capacities to store and process data. Finding ways to facilitate investigation on platforms with larger capacities for data is one of the main challenges that accompanies adjustment to increased demand. Scaling up processing power can also support automation and AI functionality to cull and score content along with ML to train systems to identify relevant data.
Faster Processing Throughput for eDiscovery
In 2022, a leading eDiscovery platform scaled a REST cluster to one terabyte per hour of processing throughput. Most end-to-end eDiscovery solutions are focusing on ways to process data more efficiently, particularly during early case assessment. Faster processing is crucial during ingestion, extraction and filtering to maximize the efficiency of downstream workflows.
Processing power and speed also impact the effectiveness of the latest innovations on eDiscovery platforms, which include active machine learning and continuous syncing. The need to scale up processing power is apparent given that the average large organization manages 347.56 terabytes of data and between 80% to 90% of enterprise data is unstructured. Cloud-based eDiscovery tools, data storage and operations can be more readily scalable than conventional on-premises approaches to managing electronically stored information.
More Automation of eDiscovery Workflows
Some of the most important adjustments that platforms for eDiscovery are making in response to increased demand involve automation. Many platforms allow users to automate a variety of repetitive tasks throughout eDiscovery workflows. Automating categorization and indexing processes enables members of a legal team to work more efficiently. Increased productivity can also result from automating communications with custodians, from hold notifications to reminders and escalations.
Automation can ensure that queries return the most relevant content. Some of the most common uses of automation across eDiscovery platforms include deduplicating and deNISTing data, through a process based on a list of file types maintained by the National Institute of Standards and Technology and the National Software Reference Library. Expanding cloud storage and processing capabilities can allow for more widespread implementation of automation, not to mention more intensive AI and ML functions.
Greater Reliance on AI and ML During eDiscovery
The latest adjustments to meet growing demand across eDiscovery platforms involve using AI and ML to expand the range of tasks and processes that can be automated in workflows. This functionality can support conceptual searching, intelligent data selection, iterative insights, predictive coding and continuous active learning. An increasing number of platforms make these features available in low- or no-code interfaces.
Giving legal teams the power to train predictive coding models to score items in review sets makes working with large volumes of data easier. The most advanced platforms learn from user decisions and randomly sample data to reduce the amount of manual input needed to categorize and index data. Decision makers for enterprises that manage large amounts of data are seeking out platforms that offer these advanced features to maximize efficiency and reduce costs.
Dedicated Resources for Modern Data Types
Scaling capacity is essential for handling a growing number of types of complex data. Evidence can now include text messages sent via SMS, MMS or messaging applications and conversational context shared in collaborative workspaces or captured during video meetings. The need to process large amounts of content originating from a vast array of platforms calls for dedicated resources on eDiscovery platforms.
Conceptual clustering and search tools are particularly useful for filtering large volumes of communication and grouping electronically stored information into manageable clusters. Iterative insights draw on AI and ML capabilities to expedite the process of working with modern data types. Legacy archives fall short when it comes to managing the growing volume and variety of information used in eDiscovery today. Cloud migration solutions enable enterprises to transform a wide variety of electronic records.
Cloud Migration and eDiscovery Platforms
Migrating data to the cloud can streamline the eDiscovery process by eliminating the need for on-premises hardware and software solutions. Most eDiscovery takes place remotely, which makes cloud-based access an advantage for many enterprises. Platforms are pursuing many adjustments oriented toward meeting customers' needs throughout the eDiscovery process. Solutions for transforming data into the cloud can also maximize returns on tech spending.
Cloudficient offers enterprise legal departments and large firms access to next-generation cloud migration solutions that facilitate processing ever-increasing amounts of data on eDiscovery platforms. We are changing the way customers retire legacy systems and transform organizations into the cloud. Our business creates product offerings that correspond to client needs and provide affordable, scalable, fast and seamless cloud migration and onboarding services. We also offer right-sized eDiscovery solutions for businesses who need to take a new, more modern approach to eDiscovery.
With unmatched next generation migration technology, Cloudficient is revolutionizing the way businesses retire legacy systems and transform their organization into the cloud. Our business constantly remains focused on client needs and creating product offerings that match them. We provide affordable services that are scalable, fast and seamless.