Beyond the answer: citations, jump links, relevance and consistency
Four capabilities separate a question-and-answer tool from a legal research experience a firm can standardise on.
Generative AI can produce an answer in seconds. For legal professionals, getting an answer is only the beginning.
Attorneys also need to know whether this is the most relevant information, whether the source can be identified, whether the supporting passage can be checked quickly, whether the citation is in the format the organisation expects, and whether similar questions will return consistently useful results.
LexGeni is designed around four capabilities that make AI-powered legal research usable in professional workflows: citation formatting, source jump links, search relevance and search result consistency.
1. Citation formatting
Finding relevant legal information is valuable, but attorneys still need to identify and work with the source behind it. A legal AI platform should do more than generate a paragraph followed by an unstructured list of documents.
Depending on the implementation, citation output can be structured to include:
- Document name
- Page reference
- Relevant section
- Supporting passage
- Source link
Different organisations have different research and review workflows, and a generic citation presentation does not serve all of them. Instead of forcing attorneys to adapt to the AI, LexGeni can be configured around the organisation’s workflow.
2. Source jump links
Imagine an AI system identifies a highly relevant argument inside a 75-page brief. Without direct source navigation, verification means reading the answer, finding the document, opening it, determining the page, searching the page, locating the passage, and only then verifying.
- AI answer
- Citation
- Source jump link
- Relevant source
- Attorney verification
The attorney gets a path back to the evidence supporting it.
3. Why jump links save real time
Even small navigation delays accumulate when an attorney is reviewing dozens of results. Jump links reduce the repetitive work of locating documents, navigating lengthy briefs, finding cited pages, finding supporting passages and verifying retrieved information.
This matters most when a knowledge base holds hundreds or thousands of lengthy documents.
4. Search relevance
A search system that returns 100 documents is not necessarily better than one that returns 10. The important question is whether the most relevant results appear first.
Semantic and conceptual search identifies documents based on the meaning and context of the query rather than relying exclusively on exact keyword matches, which matters when prior work uses different terminology.
5. Prioritise the argument, not the keyword
A brief may include procedural history, background, factual discussion, legal authorities, argument sections and conclusions. A keyword appearing in a procedural section may be far less useful than a conceptually related passage in the substantive argument.
- Where does this word appear?
- Where is this legal issue actually argued?
6. Search result consistency
Relevance is important, but so is consistency. If an attorney asks substantially the same question several times and receives dramatically different results, it becomes difficult to develop confidence in the workflow, even when some of those results are useful.
A professional legal AI solution should aim for both: high relevance and high consistency.
