Litigation need its own AI. Wexler fills the gap.
“Legal AI” often gets talked about as if it’s one product or one market. In reality, it’s made up of distinct categories, each aimed at different pain points.
Some platforms position themselves as broad assistants across practice areas, capable of drafting, summarising, or monitoring compliance. Others have gone deep into contracts, focusing on clause analysis, negotiation support, and lifecycle management. E-discovery has long been its own market, with tools designed to sift through millions of documents in disclosure (or discovery). Legal research assistants have developed from Westlaw and Lexis’s bank of legal knowledge.
Grouping all of these together under a single label makes it harder to see the trade-offs. A tool that accelerates contract drafting is designed to tolerate some error because every draft is reviewed before execution. One that cuts down disclosure sets is designed to highlight what might matter, not to decide what actually happened. Preparing for litigation requires a different standard. Every fact needs to be sourced, every inconsistency mapped, and every timeline defensible.
Here’s an overview of the main legal AI categories and the new space we’re carving out at Wexler.
Legal AI overview
- General legal AI: Drafting, summarising, compliance. Fast and versatile, but not always precise enough for specific fields like litigation, IP or real estate.
- Contract lifecycle (CLM): Drafting, negotiation, clause management.
- E-discovery: The original category of legal tech. Ediscovery prepares documents for human review, but is built on a data model that is rigidly ‘document-first’. That means key insights can go unnoticed when things get complex.
- Research assistants: Case law and memo drafting. Speeds research, but doesn’t structure the factual record.
- Fact intelligence: Dispute resolution. Extracts, links, and tests facts for accuracy and defensibility.
General legal AI
General platforms like Harvey, Legora or CoCounsel are designed for breadth. Marketing themselves as all-purpose legal assistants, they draft, summarise, monitor compliance, and review documents. They’re designed to be used across corporate, regulatory, and employment work where speed is the priority. These platforms are very useful for a wide range of tasks but perhaps suffer in the detailed, nuanced and varied processes required to tackle a complex dispute, patent & IP work, or indeed for complex real estate transactions.
Contract lifecycle tools (CLM)
Platforms like Ironclad, Juro, and Wordsmith handle drafting, clause comparison, and negotiation support. They fit transactional practice, where workflows are defined and errors can be corrected before execution. These platforms can sell to in-house teams and disintermediate law firms altogether by solving complex transactional tasks for in house teams.
E-discovery
Relativity, Everlaw, and Disco have evolved from keyword search and predictive coding to generative AI that classifies and summarises at scale. Millions of files can be reduced to thousands, saving time and cost. The challenge with eDiscovery is applying fact-level insights when the fact patterns are so varied. Where eDiscovery does a great job of preparing documents for human review, what comes next requires extensive manual work by a team of lawyers. E-discovery doesn’t tell you what actually happened, who was involved, or whether accounts are consistent.
Research assistants
Platforms like Lexis+ AI focus on legal research. They pull from curated databases to answer questions, assemble case law, or draft research memos. These are built on the enormous databases of legal knowledge that Lexis and Westlaw have compiled over decades. They have, however, been beset by issues with accuracy and hallucination. So be ensure the research assistant you use has in-built human verification of each AI source that is cited.
Fact intelligence
At ILTACON this year, the Wexler team heard time and time again that innovation leads were looking to create efficiencies and leverage specialised AI for litigation workflows. It’s no longer a competitive advantage to have a generalist legal AI system, and to develop a winning case strategy, the top firms are looking to AI systems that understand the nuance and complexity of dispute resolution.
It’s for litigators who don’t need faster drafting or broader search, but clarity over facts: which events happened, in what order, who was involved, and whether accounts hold together when tested.
Wexler treats documents as sources of facts, not endpoints. It extracts dates, actions, and relationships, links them to people and organisations, and structures them into chronologies. Contradictions are surfaced and tied back to their sources, so every inference stays grounded in evidence.
Its value spans the lifecycle of a dispute. At the earliest stage, it supports case assessment and strategy, helping teams build effective search terms. As disclosure progresses, it maps inconsistencies across statements and pleadings, helps draft motions and submissions, builds timelines and factual matrices. As hearings or trials approach, it generates chronologies, maps out the key players, and shows the contradictions that move directly into exhibits and preparation materials. Our AI assistant, KiM, can answer questions over vast document corpora, extract key information or prepare submissions.
Read more: Capture and connect every actor in your case with Wexler’s Dramatis Personae
The scope extends beyond courtroom litigation. Arbitration, regulatory investigations, and inquiries all demand a defensible factual record. In-house teams at large corporations face the same challenge when coordinating complex disputes. Until now, the only options were to manage this record manually, or to bend a general-purpose tool into workflows it was never designed to handle.
Fact intelligence provides the third option: a purpose-built category for structuring, testing, and defending facts at scale. It goes beyond document triage, contract management, or case law retrieval, giving litigators the determinism they need when outcomes hinge on precision.
When to use what
We’ve seen firms trying to bend general-purpose systems into roles they weren’t built for. The result is usually frustration. You need to match the tool to the task.
General platforms are useful when you need coverage across corporate, regulatory, or employment work. They draft, summarise, and monitor compliance well enough that imperfections can be fixed in review.
CLM tools belong in transactional practice. They help with drafting, clause comparison, and negotiation. In those settings, workflows are tightly defined and errors can be corrected before execution.
E-discovery platforms are for disclosure. They reduce millions of documents to a manageable set. That saves time and cost, but it’s still document-level work. They tell you which materials might matter, not what actually happened.
Research assistants are good for speeding up legal research. They retrieve case law, assemble memos, and answer straightforward questions. They save time but they don’t structure the factual record of a dispute.
Fact intelligence is different. It’s needed when the factual record is on the line. Assertions have to be tested directly against the documents to see if they hold. Facts need to be organised into timelines and linked to their sources so they can withstand scrutiny in court.
Wexler’s focus: find every fact
Wexler is designed exclusively for disputes. We don’t treat documents as endpoints but as sources of fact. Wexler extracts statements, connects them to people and organisations, and structures them into chronologies that can withstand scrutiny. Contradictions are highlighted and tied back to their sources.
Wexler supports the entire litigation lifecycle. It helps shape strategy from the offset, tests inconsistencies across disclosure, and equips teams for trial preparation. On security, it meets enterprise standards with ISO 27001 and SOC 2 Type II certification, single sign-on, regular penetration testing, and options for local data hosting.
Disputes need their own category of AI. General platforms, e-discovery tools, and contract assistants will remain essential in their own domains, but they don’t solve the most important challenge for any litigator: establishing the facts.
Firms including Clifford Chance, Goodwin, Addleshaw Goddard and HSF Kramer use Wexler. Get your facts straight, at scale, with AI built for complex disputes. Get a demo.