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eDiscovery Specialist

Manage privilege review and logging

Enhances✓ Available Now

What You Do Today

Coordinate privilege review, manage privilege log generation, ensure consistent privilege designations across review teams

AI That Applies

AI identifies potentially privileged documents (attorney names, law firm domains, legal terminology) and auto-generates privilege log entries

Technologies

Relativity PrivilegeEverlawLogikcull

How It Works

For manage privilege review and logging, the system identifies potentially privileged documents (attorney names. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output — privilege log entries — surfaces in the existing workflow where the practitioner can review and act on it.

What Changes

Privilege identification is AI-assisted; AI catches privileged documents that reviewers might miss and auto-drafts log descriptions

What Stays

Final privilege determinations, handling waiver issues, and the legal judgment about borderline privilege claims

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for manage privilege review and logging, understand your current state.

•
Map your current process: Document how manage privilege review and logging works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
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Identify the judgment points: Final privilege determinations, handling waiver issues, and the legal judgment about borderline privilege claims. These are the boundaries AI won't cross.
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Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Relativity Privilege tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long manage privilege review and logging takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your general counsel or managing partner

“What data do we already have that could improve how we handle manage privilege review and logging?”

They set the firm's AI adoption posture

your legal technology manager

“Who on our team has the deepest experience with manage privilege review and logging, and what tools are they already using?”

They manage the tools and can show you capabilities you don't know exist

a client who's adopted AI in their legal department

“If we brought in AI tools for manage privilege review and logging, what would we measure before and after to know it actually helped?”

Their expectations for outside counsel are shifting

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.

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