Legal Data Services
We work through the material. You work on the case.
Organize and review documents, correspondence and evidence. Build chronologies, identify key records, and connect the material your legal team needs.
What you provide
Case documents, correspondence and other records within the agreed scope.
Typical case material includes
- Pleadings and court filings
- Correspondence and email threads
- Discovery and evidentiary documents
- Prior chronologies or case notes
How the work gets done
The same four stages behind every CRUNCH engagement, applied here.
- 01
Process, organize and search the supplied material.
- 02
Review documents and extract relevant information.
- 03
Build chronologies and identify people, events and connections.
- 04
Surface key documents, inconsistencies and gaps.
What you receive
Organized, searchable case material and source-linked findings ready for legal work.
Notice period requires attention
The sample agreement requires written notice before renewal. Confirm the relevant dates against the transaction timetable.
Why this work matters
An analysis of the TREC 2009 Legal Track found that technology-assisted review processes used by two participating teams outperformed the exhaustive-manual-review benchmark based on official TREC assessors, measured through recall, precision and F1.
Maura R. Grossman and Gordon V. Cormack · 2011
This comparison concerns particular teams, processes and evaluation data. It does not establish universal performance for AI, modern generative AI or CRUNCH.
Read sourceWho this is for
Questions & answers
Questions about Legal Data Services
- Can a large document review be performed under a board, regulator or court deadline?
A review can be designed around an external deadline when the question, source set, priorities and deliverable are fixed early. Technology can help manage scale, but feasibility must be assessed per engagement.
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- How does technology-assisted review differ from linear review?
Linear review allocates human attention item by item. A technology-assisted workflow can build an index, classify, retrieve, extract and compare records across the corpus before directing human attention to relevant issues.
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- How do you review hundreds of thousands of documents?
At that scale, sequential reading alone is not a practical architecture. A technology-assisted workflow can use indexing, classification, search, extraction, grouping or deduplication where appropriate, followed by human review against scope.
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- What is Legal Data?
CRUNCH Legal Data Services work on the records behind a legal matter: documents, correspondence, evidence and prior work product. Material is organized and searchable, chronologies and connections are built, key records and inconsistencies are surfaced, and findings remain linked to source.
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- Is keyword search enough to understand a legal matter?
Keyword search can be useful, but it does not by itself connect versions, events, people and correspondence. A legal team may also need chronology building, cross-document comparison, contradiction mapping and source traceability.
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- How does CRUNCH build a legal chronology?
CRUNCH processes and organizes the source set, then connects events, people, dates and related records into a working timeline. Material entries retain a path back to supporting documents so lawyers can verify the record.
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- Does CRUNCH replace lawyers?
No. CRUNCH performs material-intensive work such as processing, organization, search, extraction, comparison and source linking. Legal interpretation, advice, strategy and professional decisions remain with lawyers.
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- What is Technology-Assisted Review?
Technology-Assisted Review, or TAR, refers to review workflows in which technology helps classify, prioritize or identify documents for human review. The term predates generative AI. Research on particular TAR processes is not a performance claim for every system or CRUNCH.
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- What is TAR?
TAR stands for Technology-Assisted Review. Technology helps organize, classify, prioritize or retrieve relevant material within a broader review process. TAR is not synonymous with ChatGPT or generative AI.
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- Did TAR exist before generative AI?
Yes. Technology-Assisted Review and computer-assisted review were used and studied in e-discovery well before the generative-AI wave. Grossman and Cormack published their widely cited paper in 2011 using TREC 2009 data.
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