By Mehdi HassanWhat is the AI startup website checklist before you fundraise?
The AI startup website checklist below is 12 pass/fail checks, grouped into five questions a first-time visitor answers in a few minutes: what is this, is it real, can I trust it with data, who builds it, and are the AI claims honest. A check passes only if a stranger can see the answer on the site without asking you.
We built it from first principles, not from a survey of investors. In our view, an investor's first visit tests what a careful buyer tests, just faster, and AI products carry extra weight because visitors arrive doubting them. Our guide to AI startup website design covers the full playbook; this is the pre-raise audit.
How do you run the audit?
Run the audit as a stranger would meet the site: on a phone, logged out, starting from a search result or a shared link rather than your bookmarks. Score each check pass or fail, with no partial credit, and write down the exact sentence or page that earns the pass.
Open the site cold
Use a private window on a phone and arrive from a search for your company name.
Read the hero once, then look away
Write down what you think the product does and who it's for. If your note doesn't match your one-liner, check 1 fails.
Hunt for proof
Look for a real output, product UI and a way to try or see it. If it sits below three sections, it's buried.
Look for the data answers
Find where the site says whether customer data trains models, where it's stored and what certifications you hold. Note how many clicks it took.
Check the people and the plumbing
Find the founders' names, a working contact route, legal pages and the most recent date anywhere on the site.
Reread every AI claim
Highlight each sentence that mentions AI, models, agents or accuracy. For each, ask whether you could show evidence for it on a call tomorrow.
Score and sort
Count fails per group and fix them in the group order below, since a visitor who can't place your category never reaches the rest.
Does your site name the category and the job?
Your site passes this group when a visitor can say, in their own words, what kind of product you are and what job it does for whom. Category comes first because every later judgment depends on it: proof, pricing and competitors only make sense once the visitor knows what bucket you're in.
Check | Pass | Fail |
|---|---|---|
1. Category in the hero | A known category or a plain comparison: 'an AI agent that reconciles invoices' | 'The intelligence layer for modern teams' |
2. Buyer and job named | A specific role and task: 'for AP teams closing month-end' | 'For businesses of every size' |
3. One message everywhere | Homepage, deck slide one and LinkedIn say the same thing | Three different one-liners across three surfaces |
Check 3 matters more during a raise than at any other time, because investors see the deck and the site side by side. If they disagree, the visitor has to decide which one is true. Our guide on how to explain an AI product on your homepage has rewrite patterns for vague heroes, and the AI company website examples show how others state the category in one screen.
Does the site prove the AI product exists?
The site proves the product exists when a visitor sees real output from it, not an illustration of the idea. AI is easy to describe and easy to fake in a mockup, so the bar is higher than for ordinary software: show what goes in, what comes out, and that someone can use it today.
Check | Pass | Fail |
|---|---|---|
4. Real output on the homepage | An actual input and the product's actual result, captioned | Abstract art, a stock robot or a glowing orb |
5. Product UI visible | Screenshots or a short recording of the real interface | Only a waitlist form and a tagline |
6. A way to see more | Signup, sandbox, docs, a recorded demo or a booked demo with clear next steps | 'Contact us' as the only route, with no idea what happens next |
If the product is early, show the narrow thing that works rather than a broad vision. A crisp recording of one workflow beats a montage of features that don't ship yet. For agent products, show a step-by-step run of what the agent did and where a human approved it; our piece on AI agent website design covers that pattern, and our AI agents industry page shows how we approach those sites.
Can a visitor find your data and security answers?
This group passes when the questions every AI buyer asks have written answers one click from the homepage. Buyers arrive doubtful: in a Crazy Egg study of attitudes toward AI tools, 97% of respondents saw benefits but only 45% said they would try one. Investors know that gap is the sales problem you'll face, so a site that closes it reads as a company that understands its market.
Check | Pass | Fail |
|---|---|---|
7. Training policy stated | A plain sentence on whether customer data trains models, with any opt-outs | Silence, or a privacy policy that never mentions models |
8. Providers and storage named | Model providers, subprocessors and data regions listed on a dated page | 'Enterprise-grade security' with nothing behind it |
9. Compliance status exact | 'SOC 2 Type I complete, Type II in progress, expected Q2' | A badge for an audit that hasn't finished |
A trust page doesn't need to be long. It needs to be accurate, dated and easy to find. Our AI trust page guide gives a section-by-section template, and the list of must-have AI startup website pages shows where it sits in the build order.
Is the team named and the company visibly real?
This group passes when a visitor can find who runs the company and confirm it's a working business, not a weekend demo. Early-stage investing is heavily a bet on the team, so in our view a site that hides the founders throws away its strongest asset at the exact moment it's needed.
- 10. Founders named, with relevant background. An about page or homepage section with names, roles, a line on why this team, and links to LinkedIn or GitHub. Anonymous sites read as side projects.
- 11. The basics work. A domain email in the contact route, a form that actually delivers, privacy and terms pages, a footer year that's current and a blog or changelog with a recent date. Each one is small; together they say someone is home.
Are your AI claims specific and true?
The final check passes when every AI claim on the site is specific enough to test and true enough to demonstrate. Vague or inflated AI language, often called AI-washing, is the fastest way to lose a technical reader, and regulators have taken notice: the Federal Trade Commission has warned companies that claims about AI must be truthful and backed by evidence.
- 12. Every claim survives a follow-up question. 'Cuts review time on standard NDAs' passes if you can show it. 'Fully autonomous', 'human-level' or 'proprietary model' fails if the product wraps a third-party model with a human in the loop.
Say what's yours and what isn't. Building on a foundation model is normal; claiming you trained one when you didn't is the kind of detail diligence finds later. Name the limits too: where the product is reliable, where it needs review and what it doesn't do.
What should you fix first if you fail several checks?
Fix failures in group order: category, proof, data answers, team, then claims, but finish the claims review before outreach starts. Category fixes are usually a short rewrite; proof needs real screenshots or a recording; data answers need a working session with whoever owns security; team and plumbing fixes are quick.
Most fails are copy and content problems, so they rarely justify a rebuild on their own. A rebuild makes sense when the site's structure can't hold the fixes, such as no room for a trust page, no CMS for a changelog, or a template that forces a vague hero. Our AI startup website cost guide covers what each route costs, and our startup website design service explains how we run a full build.
Hypothetical example: scoring a seed-stage AI startup's site
For example, suppose a seed-stage AI startup that drafts insurance claim summaries runs the audit. Its hero says 'Intelligent automation for modern insurers' over an abstract animation. It fails checks 1, 2 and 4. It has a product recording, but it's on a separate page (check 5 passes, check 6 passes). There's a privacy policy but no word on training data (check 7 fails). The founders are named (check 10 passes). One line claims 'zero hallucinations' (check 12 fails).
The fix list: rewrite the hero to name the category, buyer and job, move a 20-second clip of a real claim summary into the hero, add a short dated trust section with the training policy, and replace 'zero hallucinations' with how outputs are checked. None of that needs a new site. It needs a week of focused copy and content work.
