Wexler establishes what the evidence actually proves
Summary
- Harvey and Legora are powerful generalist legal AI tools optimised for generalist work. They use powerful LLMs as their source models, whose training data skews heavily toward contracts and corporate documents. While they excel at general tasks such as drafting, they weren't built to extract and organise the facts that determine litigation outcomes.
- Litigators are specialists managing complex, high-stakes disputes. They need purpose-built tools that match their actual workflows: identifying critical facts, tracking evidence to sources, building chronologies, and testing case theory.
- Generalist AI platforms treat documents as text to analyse rather than evidence to mine. They don't systematically extract facts, link them to sources, or map them against case issues.
- Even when pairing Harvey/Legora with eDiscovery, reconstructing a complete factual record remains manual and fragmented. Critical facts emerge late. Case theory stays untested until deep into proceedings.
- Wexler transforms vast quantities of unstructured evidence into structured fact intelligence; matching how litigation teams actually work. Every fact is extracted, source-linked, and continuously maintained in a single verifiable record. Disputes teams can stress-test case theory from day one, knowing exactly what they can prove and whether the evidence lives within the documents.
Litigators deserve specialist tools built for their specialist work, not generalist AI that forces them to adapt their workflows to the technology.
Where Harvey and Legora add value
Harvey and Legora are general AI platforms widely used by law firms. They are productivity platforms designed to help lawyers work faster and more consistently, but are not specialised to the workflows of a litigator. In disputes, they are used to:
- Summarise and tabulate evidence
- Support drafting, legal research, and reasoning
Despite these gains, the core factual work of litigation remains largely manual. Neither Harvey nor Legora is designed to:
- Maintain a persistent, evolving map of the facts as they develop
- Systematically reconcile competing accounts across the entire evidential record
- Surface contradictions as structural weaknesses in case theory
- Build accurate, source-verified chronologies from 100k+ page datasets
- Keep every factual assertion continuously linked to its evidence
- Show, at any moment, what you can actually prove
Read more: We already have eDiscovery. Why do we need Wexler?
Teams still reconstruct facts using spreadsheets, Word documents, and memory. Critical weaknesses surface late, after positions have hardened.
Wexler is for understanding the evidence in full
Wexler is purpose-built for litigation teams who need to master complex evidence. It treats facts, not documents, as the fundamental unit of analysis.
Leading disputes teams use Wexler to:
- Extract every material fact from vast evidential sets
- Build and maintain live, source-linked chronologies
- Expose inconsistencies, gaps, and timeline conflicts automatically
- Trace every fact to its precise source sentence
- Stress-test case theory against the complete factual record
- Draft submissions grounded entirely in verified facts
- Update their factual matrix continuously as evidence evolves
This creates a structured, auditable fact base that shows what the evidence actually proves, not what anyone assumes. Teams can pressure-test strategy from day one, spot weaknesses before opponents do, and prepare cross-examination knowing exactly where every fact lives. This changes outcomes.
Key differences between Harvey, Legora and Wexler
Many firms deploy these platforms as a stack:
- eDiscovery to collect and reduce data
- Harvey, Legora, or similar to accelerate review, drafting, and preparation
- Wexler to extract, verify, and maintain the factual record
Harvey and Legora help firms save time. Wexler helps firms find the facts they need.
Read more: Wexler vs The Rest - what different legal AI platforms do