Hiring for eDiscovery roles has always required more than a sharp eye for legal knowledge. When your team runs on platforms like Relativity or Reveal, the stakes are even higher. A candidate who looks strong on paper but lacks genuine hands-on experience with your core technology can slow down entire matters, create workflow bottlenecks, and cost your organization far more than the hire itself.
This guide walks you through a structured, repeatable process for evaluating eDiscovery candidates with Relativity or Reveal experience. From the first CV review to final scoring, each step is designed to help you identify professionals who can contribute from day one.
What to look for before the interview begins
Before a single conversation takes place, the groundwork you lay determines the quality of candidates who reach your pipeline. Strong eDiscovery hiring starts with a clear internal picture of what platform proficiency actually means for your specific team and workflow.
Begin by mapping out how Relativity or Reveal is used within your organization. Consider the following questions:
- Which modules or features does your team use daily, such as processing, review, analytics, or production?
- What volume and complexity of matters does your team typically handle?
- Does the role require configuration and administration skills, or primarily end-user review skills?
- Will the candidate work independently or as part of a larger eDiscovery team?
Once you have clear answers, translate them into a concise role profile that separates must-have platform skills from nice-to-have ones. This profile becomes your benchmark throughout the entire evaluation process. Without it, you risk comparing candidates inconsistently and making decisions based on gut feel rather than evidence.
Screen for platform proficiency in the CV review
The CV review is your first real filter, and it pays to be systematic. Many candidates list Relativity or Reveal under a general skills section without giving you any sense of depth or context. Your job at this stage is to look past the label and find evidence of genuine, applied experience.
When reviewing CVs for eDiscovery candidates, look for these specific indicators:
- Context of use: Has the candidate used the platform in a law firm, corporate legal department, or litigation support environment? Context shapes the nature of their experience significantly.
- Scope of responsibility: Did they manage entire matters end to end, or did they perform a single task within a larger team? Look for language like “oversaw processing,” “configured workflows,” or “managed productions.”
- Volume and complexity: References to large-scale matters, multi-party litigation, or international data sets suggest a candidate who has been tested beyond routine work.
- Platform-specific terminology: Candidates with genuine Relativity experience tend to reference features like Active Learning, Relativity Processing, or RelativityOne naturally. Reveal users may reference AI-assisted review or Brainspace analytics. Vague references to “eDiscovery software” are a flag worth noting.
At this stage, you are not making a final judgment. You are shortlisting candidates whose CVs give you enough substance to explore further. Move anyone with strong contextual indicators to the next stage, and set aside those whose platform mentions feel surface-level or unsubstantiated.
Design platform-specific technical questions
With your shortlist in place, the interview becomes your opportunity to test depth. Generic eDiscovery interview questions will not tell you whether a candidate can operate effectively in your specific environment. You need questions that are tied directly to Relativity or Reveal and that require the candidate to demonstrate real working knowledge.
Questions for Relativity experience
Structure your Relativity questions around the areas most relevant to the role. For example:
- “Walk me through how you would set up a document review workflow in Relativity for a matter with 500,000 documents and a tight production deadline.”
- “How have you used Relativity’s Active Learning feature, and what factors did you consider when deciding whether to use it over linear review?”
- “Describe a time when a Relativity processing job produced unexpected errors. How did you diagnose and resolve the issue?”
Questions for Reveal experience
Reveal’s AI-driven approach means your questions should probe how candidates think about technology-assisted review and workflow automation:
- “How have you used Reveal’s AI features to prioritize documents during review, and how did you validate the model’s output?”
- “Describe how you have configured a Reveal workspace from scratch. What decisions did you make early on that shaped the rest of the matter?”
- “What challenges have you encountered with Reveal’s ingestion process, and how did you address them?”
Listen for specificity and problem-solving in the answers. Strong eDiscovery professionals do not just describe what a feature does. They explain how they used it, what decisions they made, and what they would do differently. Vague or textbook-level answers suggest familiarity without depth.
Run a practical skills assessment
Technical interviews reveal how candidates think and communicate, but a practical assessment reveals how they actually work. For eDiscovery roles, a well-designed skills test can quickly separate candidates who have used a platform extensively from those who have only touched it briefly.
Design your assessment around a realistic scenario rather than an abstract exercise. For example:
- Provide a sample matter brief that describes the scope, custodians, and review objectives.
- Ask the candidate to outline how they would set up the workspace, including processing parameters, review batching, and quality control steps.
- If you have a sandbox environment available in Relativity or Reveal, give candidates access and ask them to complete a defined task within a set timeframe.
- Follow up with a short debrief where the candidate explains their decisions and flags any challenges they encountered.
The debrief is often more revealing than the task itself. A candidate who made a misstep but can clearly articulate what went wrong and how they would correct it demonstrates the kind of reflective, problem-solving mindset that holds up under the pressure of live matters. Look for that quality as much as technical accuracy.
Keep the assessment proportionate to the seniority of the role. A junior reviewer does not need to demonstrate workspace configuration skills, while a senior litigation support specialist or eDiscovery project manager should be able to speak to end-to-end matter management with confidence. Explore open eDiscovery roles to get a sense of how the market currently frames these responsibilities.
Validate experience through targeted reference checks
Reference checks are frequently treated as a formality, but for eDiscovery hiring they are one of the most valuable tools available to you. A well-structured reference conversation can confirm or challenge everything you have learned about a candidate’s platform experience up to this point.
Rather than asking open-ended questions that invite generic praise, focus your reference conversations on specific, verifiable details:
- “Can you describe the types of matters this person supported and their specific role in the eDiscovery workflow?”
- “How comfortable were they working independently in Relativity or Reveal? Did they require significant guidance on platform tasks?”
- “Were there any situations where their technical approach needed to be corrected or redirected? How did they respond to that feedback?”
- “Would you rehire this person for a role requiring strong hands-on platform experience? Why or why not?”
Pay attention to hesitation, vagueness, or overly scripted responses during reference calls. These can signal that the referee is being careful not to say something negative rather than genuinely endorsing the candidate. A strong reference for an eDiscovery professional should include concrete examples and a clear sense of the candidate’s technical contributions.
Score and compare candidates consistently
Once you have completed interviews, assessments, and reference checks, the final step is to evaluate your eDiscovery candidates against each other using a consistent framework. Without a structured scoring approach, hiring decisions tend to favor whoever made the strongest impression in the room rather than whoever demonstrated the strongest skills.
Build a simple scorecard that reflects the role profile you defined at the outset. Include weighted categories such as:
- Platform proficiency: Depth of hands-on Relativity or Reveal experience based on the interview and assessment
- Problem-solving and adaptability: How the candidate handled complex or unexpected scenarios
- Communication and collaboration: Ability to explain technical decisions clearly to legal or non-technical stakeholders
- Matter management experience: Scope and complexity of past eDiscovery work
- Cultural and team fit: Alignment with how your team operates and communicates
Score each candidate independently before discussing as a group. This reduces anchoring bias, where one person’s opinion disproportionately shapes the group’s view. Once individual scores are submitted, compare them and use the gaps as a starting point for structured discussion rather than a free-form debate.
After scoring, revisit your reference check notes alongside the scorecard. If a high-scoring candidate received a lukewarm reference on platform independence, that is worth weighing carefully before extending an offer. The goal is to make a decision that holds up not just on paper but in the day-to-day realities of your eDiscovery environment. If you are working with external partners on your search, sharing this scorecard with them ensures everyone is aligned on what a successful hire looks like. You can explore how specialist partners approach eDiscovery staffing solutions to see how structured evaluation fits into a broader hiring strategy.
How Iceberg supports your eDiscovery hiring process
Evaluating eDiscovery candidates with genuine Relativity or Reveal experience takes time, structure, and access to the right talent pool. That is where we come in. At Iceberg, we specialize exclusively in eDiscovery and cybersecurity recruitment, which means we understand the platform nuances, role expectations, and market dynamics that generalist recruiters often miss.
When you partner with us, you get:
- Access to a global network of over 120,000 eDiscovery professionals across 23 countries
- Pre-screened candidates with verified, platform-specific experience in Relativity, Reveal, and other leading eDiscovery tools
- A structured approach to matching candidates to your team’s specific workflow, culture, and matter complexity
- A 98% placement retention rate, meaning the professionals we place stay and grow within their roles
- A complimentary Vacancy Health Check to help you diagnose exactly where your current hiring process is falling short
Whether you are filling a single specialist role or building out an entire eDiscovery function, we help you move faster without compromising on quality. Get in touch with our team to start the conversation.
