Ask any Relativity administrator what slows them down, and you’ll usually get the same answer: manual storage management. Every few weeks, someone has to check which workspaces are inactive, decide what to move, run archive jobs, and then double-check that nothing breaks in the process. It’s repetitive and error-prone and eats up time that could be spent improving workflow efficiency.
But that’s changing. Relativity’s storage automation options, from ARM jobs to Cold Storage and Data Grid, now enable teams to set smart, rules-based triggers. These workflows handle archiving, migration, and restores without human intervention. The result is smoother transitions between Repository, Review, and Cold Storage while cutting costs and improving performance.
This article explains how these storage types work, why automation matters, and how teams are using them to boost workflow efficiency in real-world environments.
Before talking about automation, it helps to understand the function of each storage type.
1. Repository Workspaces
Repository storage is the staging area, the first stop for data before it moves into full review. It’s cheaper than active Review storage and great for early case assessment or analytics work. Think of it as your preparation zone before you commit to the full Review cost.
2. Review Workspaces (Active)
This is where the real action happens. It’s the most resource-intensive storage type because reviewers are actively coding, searching, and analyzing documents. That’s why it’s important to move workspaces out of Review once activity slows down.
3. Cold Storage
Cold Storage is designed for inactive workspaces that may need to be accessed later. You can archive directly from Cold Storage or restore a case that reopens. The biggest benefit is that it keeps your data accessible while reducing overall costs.
4. Data Grid (Powered by Elasticsearch)
Data Grid stores extracted long text and audit data separately from SQL. This keeps your database light and your searches fast. It’s especially useful for scaling large environments, as audit tables can get massive over time.
By automating transitions between these types, you stop paying Review rates for inactive data and improve overall system responsiveness.
Automation in Relativity starts with one simple idea: Let the system handle predictable work. Every workspace has a natural lifecycle of ingestion, review, closure, and archiving. Each phase requires different storage behavior, and automation maintains that consistency.
Here’s what workflow efficiency improves:
Each step replaces hours of manual checking, helping admins focus on value-added tasks. For developers, Relativity’s API documentation explains how to safely automate ARM and Cold Storage operations.
Every organization handles data differently, but most fall into one of these common automation models:
These patterns save time and mistakes, which are the biggest threats to workflow efficiency in large-scale environments.
Automation can go wrong if the order of actions isn’t correct. The good news is that Relativity’s documentation covers best practices. Here are a few to keep in mind:
By following these guardrails, you’ll keep automation reliable while still improving workflow efficiency.
Let’s walk through how to set up a basic storage automation model that links activity triggers to storage actions.
1. Define Your Policy
Decide what inactivity means for your team—for example, no user activity in sixty days. Then, set your retention rules, such as keeping archived data for three years.
2. Enable the Tools
Install the Automated Workflows app. Confirm ARM and Cold Storage API access. If you’re on RelativityOne, make sure the Data Grid Text Migration app and its agents are active.
3. Create the Triggers
Set a daily automated check to calculate “days since last document view or coding activity.” If it exceeds your threshold, the workflow fires the next action.
4. Chain the Actions
5. Test Before Rolling Out
Start small. Use a low-risk workspace and monitor the process. Check dtSearch functionality, audit logs, and access controls after the automation completes.
6. Plan Rollback Steps
Document your restore plan. You can use ARM Restore jobs to bring back any workspace, but always verify indexes and permissions afterward.
These steps will give you a baseline automation that immediately boosts workflow and consistency across your Relativity environment.
Once automation is live, the benefits are visible almost immediately:
For context, automated lifecycle management can cut operational costs by up to 30% in large data platforms. That same principle applies in Relativity environments but with less manual work, more structured control, and better use of admin time.
If you manage a large RelativityOne environment, consider going beyond simple triggers:
Automation isn’t about removing people from the process; it’s about removing friction. When you automate Relativity’s storage types, you connect system behavior to business logic. Workspaces move, archive, and restore based on actual activity, not someone’s reminder note.
That’s where workflow efficiency becomes more than a buzzword. It’s measurable. You can spend less time managing systems and more time reviewing data, serving clients, and meeting deadlines faster.
Storage automation turns Relativity from a tool that you manage into a system that manages itself. CaseFlow is a Relativity application that automatically transitions your cases to the different lifecycle stages. Once it’s in place, you’ll wonder how you ever worked without it.
Stop letting inefficient processes drain your firm's profitability. Every hour spent on manual case management and disorganized workflows is an hour that could be spent generating revenue. Your clients deserve better, and so does your bottom line. CaseFlow delivers streamlined case management, automated workflows, and real-time insights that free your team to focus on what matters most: practicing law profitably. Ready to drive real efficiency and savings? Discover how CaseFlow can transform your firm's operations.