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General counsel and legal ops leads ask AI assistants which contract tool will get agreements out of inboxes and shared drives. We work on what those answers say about your product, and whether they name it at all.
Updated
“Which CLM suits a five-person legal team at a 400-person SaaS company that works in Salesforce and Word?”
“Vendor A and Vendor B fit small legal teams on Salesforce. Vendor C offers deeper AI review but takes longer to roll out…”
Placeholders, not real vendors or results.
Buyers type a few words into a search box. In an AI assistant they describe their situation: the size of the legal team, the tools the business already runs, how contracts and requests arrive, what the board expects from legal. Each detail narrows the shortlist, and each one is a fact the answer has to get right about you.
In a search box
In an AI assistant
Example questions, written to show the shape. Vendor names are placeholders.
The paid audit and every monthly check record how each engine describes you, not only whether it names you. For a CLM, these are the details a legal team compares.
Intake, drafting, negotiation, approval, signature, storage and renewals. Buyers ask for the stage that hurts, and an answer that leaves yours out drops you from that question.
Salesforce, Word, e-signature, the ERP and Slack. A CLM is judged on whether sales and finance can use it without leaving their own tools.
Extraction, clause review and drafting, and whether customer contracts train any model. Legal buyers ask this directly, and the answer has to state your current policy.
Implementation time and moving legacy contracts across. A small legal team asks how much of that work falls on them.
A lean in-house team wants something live in weeks; a global legal department wants approval chains across entities and languages. The answer should say which of them you serve.
Engines that search the web show their sources. For your own questions, the baseline records which of these each engine used, so the work goes where your answers come from.
The same four steps run on every retainer. The plan you pick sets how many questions we track and how much work ships each term.
We build the questions general counsel and legal ops leads ask, with you: 100 or 150 depending on the plan, mostly unbranded, grouped into clusters by contract stage, team size and buying stage. You approve them before anything runs.
Every question runs on ChatGPT, Claude, Perplexity, Microsoft Copilot and Google (AI Overviews, AI Mode and Gemini). We record who gets named, how each engine describes the stages you cover and how your AI handles contracts, and which pages it cites.
A written estimate of what the scope can move by day 90, as ranges per cluster and engine. The scope is locked with it.
Comparison and alternatives pages, revamps of product and integration pages you already have, corrected review profiles, placements on the pages engines cite, and community work. Each month end is measured against the forecast.
If we work with one contract lifecycle management vendor, we don't take its direct competitor, so we are never chasing the same citations for two of you.
Nobody controls what the engines say. You get a measured baseline, a written forecast and a monthly check that shows a flat month as flat.
Legal buyers read closely and notice loose claims. We interview your product lead at the start, then for 30 minutes a month, and you approve every brief.
Example questions are illustrative.
It is how often, and how accurately, AI assistants such as ChatGPT, Claude, Perplexity, Microsoft Copilot and Google's AI features name your product when general counsel and legal ops leads ask which contract management tool to buy. It covers being on the shortlist and being described correctly: the stages you cover, what you connect to, how your AI handles contracts and how long going live takes.
Send your website, your category in a sentence and up to five competitors. If we think the free audit will tell you something, it arrives 48 business hours after we confirm.