Use Cases
Using AI to Draft Contracts, with a Policy Layer
AI drafts fast. The problem is that the output is new language your organisation has never approved. The liability cap in that draft may not match your policy. The governing law clause may not reflect your standard position. The indemnity language may be something your GC has never seen. It sounds right. It may not be right for you.
Why AI contract drafting outruns legal review
Legal teams are using AI for drafting. They are drafting faster than ever. But speed without governance creates a new risk: AI-generated language that no qualified lawyer has reviewed is reaching counterparties.
General-purpose AI models are not aware of your organisation's approved clause language. They do not know your GC approved a specific liability cap last quarter. They do not know your standard termination notice period. They generate language that is legally plausible and often wrong for your specific standards.
The result: lawyers are manually checking every AI-generated draft against a policy that lives in a separate document, an email thread, or institutional memory. The time saved in drafting is spent in verification.
How the policy layer works during drafting
Connect Lexnus to your AI model via MCP
Lexnus exposes its policy engine and clause library as an MCP server. Once connected, the AI model can call Lexnus during a drafting session without the lawyer switching tools or applications.
When a lawyer asks the AI model to draft a liability clause, it calls Lexnus's lexnus_search_clause_library tool to find the organisation's published liability language, or lexnus_get_playbook_clauses to get the full approved clause set for the contract type at hand. The AI model drafts from those. The output is not generated from scratch. It comes from your governed library.
Evaluate as you draft
As the draft develops, the AI model can call lexnus_analyse_document to run the current text against your playbook, then lexnus_check_rule_violations to see what is still open. Each finding names the rule that fired, quotes the text that triggered it, and says whether it blocks signature.
This happens inline, during the drafting session. The lawyer does not need to export the document, upload it separately, or run a separate review step.
Run a full compliance check before sending
Before the draft leaves, the complete document is submitted to lexnus_analyse_document. Lexnus runs a full analysis against your active playbook. Every rule is checked. Every gap is identified. The lawyer reviews the flagged items, not the full contract, and the compliant draft goes out.
What changes when AI drafts against a playbook
Before Lexnus: AI drafts fast. The lawyer manually verifies each clause against a policy that lives in a separate document, an email thread, or institutional memory. Some things get missed. The same issues recur.
With Lexnus: The AI model drafts from your approved clause library. Clause evaluation runs inline. Full compliance check before send. The lawyer focuses on the exceptions and edge cases that actually require judgement.
The audit trail shows every call the AI model made to Lexnus: which tool, when, and whether it worked. Analysis results stay on the contract's own record. The GC has visibility into what AI is doing with the organisation's contracts.
Who needs a policy layer over AI drafting
In-house lawyers and associates who are already using AI for drafting and want to stop spending time on manual policy verification.
General Counsel who want AI drafting to happen under governance, not in a shadow workflow they cannot see or control.
Legal Ops teams building standardised contract workflows who want AI to do the heavy lifting without giving up policy control.