How do you automate the eDiscovery workflow?

You automate an eDiscovery workflow by removing manual handoffs at each stage - scripted ingestion and processing, rules-based culling, AI-assisted first-pass review, and templated production - while keeping human sign-off at the decisions that carry legal risk.

Automating an eDiscovery workflow means reducing the number of times a person has to move data, re-enter a decision, or repeat a step by hand. Very little of the process needs to stay fully manual, but almost none of it should run fully unattended either.

Where automation usually pays off:

Ingestion and processing. Scripted, repeatable intake - deduplication, email threading, OCR, exception handling - removes most of the manual setup work and makes results consistent from matter to matter.

Culling. Date ranges, custodian filters, domain exclusions, and file type rules can be applied as a standing recipe rather than rebuilt for every case.

First-pass review. Technology-assisted review and generative AI can code or rank documents against a defined criterion, so reviewers spend their time on the documents that actually need judgment instead of reading everything in arrival order.

Quality control. Automated sampling and consistency checks catch coding drift far earlier than a manual audit at the end of a review.

Production. Production specifications, numbering, redaction burning, and load file generation are highly rule-driven and rarely need a person once configured.

The parts worth keeping human: scoping decisions, the responsiveness and privilege criteria themselves, privilege calls, and final sign-off before anything leaves the building. A defensible automated workflow is one where every automated step is documented, repeatable, and auditable - so you can explain later what the system did and why.

To see automated first-pass review in practice, book a Claira demo.

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