Use case

eDiscovery and litigation document review.

From the field, AI native workflow redesign of ediscovery review process within Litigation Legal function.

Get the playbook
Convolving expertise

A senior Convolving delivery team partnered with the litigation function for one sprint. Operators from our expert network – with eighty combined years inside in-house Litigation and eDiscovery programmes – reviewed the redesign at each checkpoint. Forward-deployed engineers built inside the team's existing review platform and matter management stack. One flat fee, artifact out, no retainer creep.

Situation

Today associate and contract-attorney review runs over every document regardless of relevance density. Cost scales with volume, not with case importance.

Review accounts for seventy to eighty percent of the roughly forty-two billion dollars a year US eDiscovery spend, so the reduction lands directly on the largest cost line. Relativity aiR runs across more than two thousand projects and one hundred and ninety million review decisions, with reported fifty to seventy percent time savings, up to eighty percent review-time reduction, and ninety percent and above recall. EDRM and Exterro practitioner studies show TAR 2.0 and continuous active learning workflows cutting reviewable volume forty to sixty percent. Privilege-log accuracy and responsiveness consistency degrade across large reviewer pools, while volume growth from Slack, Teams, mobile, and video outpaces manual capacity.

Reviewable volume 100% Documents that reach first-pass review
Review cost share 70–80% Of total eDiscovery spend
Time per million docs 8–12 weeks Linear-cost contract attorney review
Privilege log accuracy 70–80% Consistency across reviewer pool

Click any node to see the activities and tools behind it. Open the canvas in fullscreen for the horizontal view.

Complication

Largest obstacles and inefficiencies.

Review consumes seventy to eighty percent of eDiscovery spend.

On a roughly forty-two billion dollar a year US market, first-pass review is the largest cost line. Linear-cost staffing means the bill scales with volume, not with case importance.

Privilege-log accuracy drifts across the reviewer pool.

Consistency lands at seventy to eighty percent when staffing scales to hundreds of contract attorneys. Production quality and defensibility risk move in step.

Modern data sources outpace manual capacity.

Slack, Teams, mobile, and video grow faster than reviewer headcount can absorb. Hot-document surfacing for deposition prep stays a separate manual pass downstream.

Resolution

The AI-native cycle.

Same six steps. Click any node to see what the redesign does in that step.

Reviewable volume 40–60% ▼ 40–60% vs today
Review cost share 20–30% ▼ ~50 points vs today
Time per million docs 2–3 weeks ▼ 70–80% vs today
Privilege log accuracy 95%+ ▲ ~20 points vs today
Key changes

What the redesign actually shifts.

Cycle compression

  • Time per million documents drops from eight to twelve weeks toward two to three.
  • Reviewable volume falls forty to sixty percent before the first reviewer opens a document.
  • Hot-document surfacing folds into review rather than a separate downstream pass.

Cost discipline

  • Review's share of eDiscovery spend drops from seventy to eighty percent toward twenty to thirty.
  • On a forty-two billion dollar a year US market, the reduction lands on the largest cost line.
  • Contract-attorney staffing scales with case importance, not document volume.

Quality and defensibility

  • Recall holds at ninety percent and above on the Relativity aiR benchmark.
  • Privilege-log consistency rises from seventy to eighty percent toward ninety-five percent and above.
  • QC runs continuously across the full corpus, not in sample batches.

Audit and control

  • Every coding decision logs the model version and reviewer override.
  • Chain of custody captures automatically across modern data sources.
  • Production sign-off captures in one review queue, not an email chain.

Deploy this in your team.

The redesign above ships as a step-by-step playbook. Process map, TAR protocol, privilege-review prompt library, QC controls register, defensibility memo, and the rollout cadence we use on engagements.

Get the playbook Or book a coffee