Clarity
Fix firstDo they understand what you do?
11 could name what kind of product this is, unprompted.
https://iprally.com/15 AI-simulated buyers
Your message lands: they know what it is, who it's for, why it's worth their time, and why to pick you.
Do they understand what you do?
11 could name what kind of product this is, unprompted.
Can they tell what it solves, and who it's for?
15 could quickly tell what problem it solves and who it is for.
Do they actually want it?
15 would take a meeting to learn more.
Is there a reason to pick you over the alternatives?
13 could name a reason to pick you over a similar option.
Your page describes: Patent search and prior-art intelligence. They said:
7 couldn't name one; 4 named the wrong one; 4 got it right.
Four separate measures, not stages: all 15 personas answered all four questions. Each square is one persona.
Two respondents flagged an internally inconsistent founding date and the absence of firmographic detail on headcount, funding, and which offices are actually paying customers. Not one of the four layers, and it does not affect the scores above or the order to fix them in.
These are 15 simulated buyers. Want 15 real ones?
Test with humansThe first is on your weakest layer, the second on the next, the third on the layer the most buyers had a problem with. Each says what to change on the page and why, with one simulated answer behind it.
Why: "Patent engine" leaves readers guessing whether this is a search tool, an agent, or a drafting assistant. Say what it is in the H1: patent search and prior-art analysis you can run in the app, in your AI tool, or over the API.
3 of 15 raised this
“The "75% time saved" and "millions of patent answers a month" numbers have zero methodology behind them”
Why: The testimonial and time-saving format matches every other patent vendor's pitch, so it gives no reason to pick this one. Name the customer, the attorney or analyst role, and the specific search that got faster.
2 of 15 raised this
“The testimonials and "75% time saved" are identical noise to what every search vendor on my shortlist says, so they don't differentiate anything”
Why: Every worked example is consumer electronics, so corporate IP teams in industrial sectors cannot see their own filings in it. Run one demo on a mechanical or chemical case, such as the pyrolysis claim already on the page.
2 of 15 raised this
“I'd need my own company or a close comparator named on the page — not just Unilever and Melexis as logos, but something like "used by in-house IP teams at consumer electronics companies managing 5,000+ patent families"”
These landed. Keep the wording when you edit around it.
The hero line and audience segmentation make the buyer and job-to-be-done immediately…
“between the use-case questions ("Who's patenting near us?", "Is this claim ready to file?") and the testimonial job titles, I had it pinned down within the first screen or two”
The demo screens do the explanatory work the copy does not
“They showed a concrete example — a wearable hydration-sensing smartwatch FTO screen across US/China/Europe pulling five active families with claim-level mapping — which is the kind of mechanism detail that actually tells me how it works”
Why: The page states savings and statistics without saying where the numbers come from or who measured them. Put the sample, the date and the method in a short line directly beneath each figure.
3 of 15 raised this
“The "75% time saved" and "millions of patent answers a month" numbers have zero methodology behind them”
Why: The demo output shows "ai_score": 0.82 with no explanation of what the number measures or its range. Add a one-line caption saying what the score ranks and how to read it.
3 of 15 raised this
“The "75% time saved" and "millions of patent answers a month" numbers have zero methodology behind them”
No specific edits needed here — this layer held up.
A deliberately adversarial read of the same answers. Each claim was checked back against what the personas said and dropped if nothing supported it.
The page's own copy is the weakest asset on it — the screenshots are carrying the argument.
Three respondents credited demo artefacts (claim numbers, confidence scores, the FTO example) with making the product understandable, while three others found the written positioning muddled across search engine, agent and drafting assistant. The prose is a…
Every number on the page is unusable as persuasion because none of it is sourced or tested against the buyer's own portfolio.
Four respondents flagged percentage claims with no methodology or sourcing, and four more said time savings would not be believed until run on their own patents and claims. That is over half the sample refusing the quantitative case.
The proof format is so generic it actively invites comparison shopping rather than ending it.
Two respondents said the testimonial and time-saved structure is identical to every other vendor pitch, and the unexplained ai_score metric was named a rule-out risk. Undifferentiated proof plus an opaque metric gives buyers no reason to stop looking.
The page offers no path to the validation it admits buyers require.
Four respondents said they must test time savings against their own prior art before accepting them, yet the page leans on unsourced percentages and interchangeable testimonials instead. The stated objection has no on-page answer.
The page sells to a narrow slice of the market it claims to address and tells everyone else they are not the customer.
Two respondents wanted evidence of enterprise scale rather than law firm caseloads and dismissed the smartwatch demo as irrelevant to industrial sectors. The same demo screens praised for clarity are the ones scoping the audience down.
Basic credibility is unforced-error territory: a contradictory founding date undercuts the precision the demo works to establish.
Two respondents found an internally inconsistent founding date and no firmographic detail on headcount, funding, or paying offices, while others contrasted precise technical demo detail against vague marketing percentages. Sloppy facts make the vague numbers…
Percentage and statistic claims carry no methodology or source
3 of 15
“The "75% time saved" and "millions of patent answers a month" numbers have zero methodology behind them”
“it undercuts itself with unsourced big numbers like "75%" and "Millions" sitting right next to the specific stuff, like marketing got hold of the page after the product team wrote the demo screens”
“that "three hours per search compared to a day and a half" line from the Melexis guy is the kind of thing that would actually get attention if I could see the underlying numbers, not just a pull quote. But right now it's one customer's testimonial with no methodology behind it, same with the generic "75%" time-saved stat repeated twice with no source.”
The product category wobbles between search engine, agent, and drafting assistant
3 of 15
“I'd call it a patent intelligence and prior-art search tool, not a new category — it's an incremental AI layer on search and drafting workflows I already use”
“the page mixes metaphors — "the patent engine for humans and their AI agents" plus "Launch agent" plus "Ask anything" plus the MCP/API line all describe the same product from three different angles, so I had to mentally merge "search engine," "agent," and "drafting assistant" into one thing myself instead of being told directly.”
The demo screens do the explanatory work the copy does not
3 of 15 · what worked
“They showed a concrete example — a wearable hydration-sensing smartwatch FTO screen across US/China/Europe pulling five active families with claim-level mapping — which is the kind of mechanism detail that actually tells me how it works”
“semantic search that actually clusters prior art by technical approach (like the hydration-sensing example, splitting optical vs. bioimpedance vs. sweat-based families) and an FTO screen that comes back with jurisdiction-filtered, active-rights-only results in minutes instead of days”
Testimonials and time-saved claims read as interchangeable with competitors
2 of 15
“The testimonials and "75% time saved" are identical noise to what every search vendor on my shortlist says, so they don't differentiate anything”
“the "ai_score": 0.82 line in the API snippet is a rule-out risk for me — if that score isn't explained (what's it weighted on, claim language, classification, citation graph?) I'll assume it's a confidence number dressed up to look rigorous”
“they sound like they promise an audit trail back to source documents, but the page never explains what that evidence trail actually contains or how it's validated against examiner reasoning”
The examples skew to law firms and consumer products, leaving enterprise and industrial…
2 of 15
“I'd need my own company or a close comparator named on the page — not just Unilever and Melexis as logos, but something like "used by in-house IP teams at consumer electronics companies managing 5,000+ patent families"”
The hero line and audience segmentation make the buyer and job-to-be-done immediately…
5 of 15 · what worked
“between the use-case questions ("Who's patenting near us?", "Is this claim ready to file?") and the testimonial job titles, I had it pinned down within the first screen or two”
“the hero line "Find prior art, build competitive intelligence, and protect new inventions, wherever you work" tells you the job to be done right away, and the logo line "Trusted by patent offices, Fortune 500 companies, and AM Law 200 firms" plus the "For Corporates" / "For Law Firms" sections spell out exactly who it's for”
“The hero line — "The patent engine for humans and their AI agents" with the subline "Find prior art, build competitive intelligence, and protect new inventions, wherever you work" — told me the problem (inefficient, keyword-limited prior art and FTO searching) and the three jobs it does”
“there are literally separate sections "For Corporates" ("Your IP function, always on, and always under your control") and "For Law Firms" ("Draft with the closest prior art on the page... thorough enough to defend")”
“The "for" is spelled out explicitly further down too — "For Corporates" and "For Law Firms" sections literally segment the two buyer types, with tailored pitches”
Time-savings claims will not be believed until tested on the buyer's own prior art
4 of 15
“The "75% time saved" and "three hours per search compared to a day and a half" quotes are the kind of number I'd want to pressure-test with our own prior art set before I believe it, not take on faith from a case study blurb.”
“I'd want them to run it live on two or three of our actual energy-sector patents and compare the output to what our last outside counsel search found, not another case study with Unilever or Melexis numbers I can't audit”
“that "three hours per search compared to a day and a half" line from the Melexis guy is the kind of thing that would actually get attention if I could see the underlying numbers, not just a pull quote. But right now it's one customer's testimonial with no methodology behind it, same with the generic "75%" time-saved stat repeated twice with no source.”
Company facts are thin and in one place contradictory
2 of 15
“"Since 2018... Over 8 years of experience" doesn't even add up cleanly”
“What would make me more confident on the "who are they" question is firmographic detail they don't give — headcount, funding, how many of those "six major patent offices" are actually paying customers versus pilots”
15 AI-simulated personas matched to your target market. Each answered independently, without seeing your goal, the scoring criteria, or each other’s answers. Attribution is role, industry and company size only.
Every answer on this page was written by an AI model role-playing a buyer profile, scored on Wynter’s B2B Message Layers framework. The personas were sampled in code across role, industry, company size and behavioral traits; the model wrote only the answers. Scores arrive through fixed verdict categories and the counts are computed in our own code, so no number here was written by a model.
The count is how many personas cleared the bar on each question. A yes can be unhesitating or come with reservations; the scorecard counts both as a yes, and this is the only place the difference is shown. Per layer:
These answers are AI-simulated and directional. Validate anything you’re betting on with real buyers, your ICPs.
A detailed, section-by-section message test report from verified B2B professionals who are actually in-market for what you sell.







