Large Data Set eDiscovery Processing
Processing and review preparation built for high-volume, document-heavy matters — applying early case assessment, deduplication and filtering to reduce volumes proportionately before review.
Who this service is for
For legal teams facing large, complex datasets where cost and timescale must be controlled without compromising defensibility.
- Litigation teams on document-heavy disputes
- Corporate legal teams in major investigations
- Regulatory and competition lawyers
- Arbitration teams with cross-border data
- eDiscovery and legal-technology managers
What this service includes
- Early case assessment to understand the dataset
- Deduplication and de-NISTing at scale
- Date-range, keyword and custodian filtering
- Email threading and document-family handling
- Chat and short-message normalisation
- Review-ready exports for high-volume review
Typical data sources
We work with the data sources most often encountered in this type of matter:
- Email & Microsoft 365
- Servers & shares
- Cloud storage
- Mobile & chat data
- Structured exports
- Large native-file sets
Why defensibility matters
Scale must not come at the cost of defensibility. We apply consistent, documented processing across the dataset, so reductions through deduplication and filtering are transparent, proportionate and explicable — and the review set remains reliable.
How the workflow operates
- Early case assessment of the full dataset
- Deduplication and de-NISTing at scale
- Targeted date, keyword and custodian filtering
- Threading and document-family validation
- Normalisation of chat and short messages
- Review-ready export and production support
Deliverables
- Reduced, proportionate review set
- Early case assessment outputs
- Deduplicated and filtered data
- Relativity-ready exports
- Processing documentation for defensibility
Frequently asked questions
How do you control review cost on big matters?
Early case assessment, deduplication, de-NISTing and targeted filtering reduce volumes proportionately before review, cutting cost and time.
Is large-scale processing still defensible?
Yes. Consistent, documented processing keeps reductions transparent and proportionate, preserving defensibility.
Can you handle mixed data types at scale?
Yes — email, documents, mobile and collaboration-platform data, including normalisation of chat into RSMF.
Control volume without losing defensibility
Talk to us about processing and preparing a large dataset for proportionate review.