By Mehdi HassanWhat pages does an AI startup website need?
An AI startup website needs seven core pages: homepage, how it works, at least one use-case page, pricing, a trust page, about, and a contact or demo page. It should add an evals page and a limitations section once it has honest material for them. The order matters, because early-stage teams rarely have time to build everything at once.
This checklist is part of our AI startup website design series. The common thread is that every page should reduce a buyer's doubt about whether the product works and whether their data is safe.
What is the full AI startup website pages checklist?
Here is the full list, with the job each page does and when to build it. The "skipped" column flags the pages most AI sites leave out, which is exactly why they're worth having.
Page | Job it does | Build | Often skipped |
|---|---|---|---|
Homepage | Name the job, show output, answer data | Launch | No |
Use-case pages | One buyer, one task, one proof | Launch (top one) | Yes |
How it works | Explain inputs, steps, human review | Launch | Sometimes |
Pricing | Explain credits, seats or usage | Before selling | No |
Trust / data policy | Training, retention, providers, security | Before enterprise deals | Yes |
Evals or benchmarks | Show how quality is measured | When results are honest | Yes |
Limitations | Say what it doesn't do | Launch, can be a section | Yes |
About | Who built it and why | Launch | No |
Contact or demo | One way to start | Launch | No |
Other industries need their own extras. Compare with our checklists for fintech website pages, digital health website pages and cybersecurity website pages if your AI product sells into a regulated market.
In what order should you build AI website pages?
Build AI website pages in the order buyers need them: first the pages that explain and prove the product, then the pages that support a purchase, then the pages that support scale. A startup that launches with a homepage, one use case and a trust line can sell. One that launches with a blog and a careers page usually can't.
- Homepage. The job in one line, a real output, a data line and one call to action. Our guide to explaining an AI product on your homepage covers the copy.
- Your top use-case page. The single buyer and task most likely to convert. Write it like a landing page.
- How it works. Inputs, steps, where a human reviews, what the output looks like.
- Pricing. Explain the unit you charge for before buyers have to ask.
- Trust page. Data use, training, retention, model providers, subprocessors and security status.
- Limitations section. On the how-it-works page or its own page.
- More use-case pages. One per buyer or task as you find them.
- Evals page. Once you have results you're willing to show with a method.
- About, careers, blog. Support pages that matter more as you grow.
What goes on a model and data policy page?
A model and data policy page says plainly whether you train on customer data, how long you keep it, which model providers process it, who your subprocessors are, and what security certifications you hold or are working toward. It's the page enterprise buyers ask for first, and the one most AI startups don't have until a deal stalls.
Our 2026 research found trust-center best practice is consistent: certifications prominent, a subprocessor list, and a page kept current. Keep the homepage version to one line linked to the full page. The AI trust page template gives you fill-in sections, and our guide to B2B trust pages covers status and compliance pages more broadly.
How should AI use-case pages be structured?
Each AI use-case page should cover one buyer and one task: the problem in their words, what the product does about it, a real example output, how it fits their existing tools, the limits for that use case, and a call to action. Answer the main question in the first lines, so search engines and AI answers can quote it.
That answer-first structure is what gets pages cited. Our guide to answer-first content structure explains the pattern, and how to build an AI-search-ready website covers the crawlability and structure side.
For example, suppose an AI startup drafts security questionnaires
For example, suppose a startup's AI drafts answers to vendor security questionnaires. Its use-case pages might be: one for security teams at SaaS companies ("Answer security questionnaires from your existing policies"), one for sales engineers ("Stop waiting on security to unblock deals"), and one for compliance leads ("Keep every answer tied to a source document").
Each page shows a sample questionnaire answer with its source policy, explains that a human approves every response, and lists the questionnaire formats it supports. This is a hypothetical example to show the structure.
Should an AI startup publish an evals or limitations page?
Yes, when you can do it honestly. An evals page that states what you measured, on what data and against what baseline makes accuracy claims believable. A limitations page or section that says what the product doesn't do filters out bad-fit users and shows you understand your own product. Both are rare, which is why they stand out.
Pros
- Gives buyers evidence instead of adjectives
- Answers questions technical evaluators would ask anyway
- Reduces churn from users who expected something else
- Signals confidence and maturity to enterprise buyers
Cons
- Competitors can see where you're weaker
- Evals go stale as models change, so they need upkeep
- A poorly explained method invites more doubt
- Takes engineering time to prepare honestly
If your results aren't ready, publish the limitations section first. It costs nothing but honesty, and it reassures buyers more than another vague accuracy claim.
How many AI startup website pages do you need at launch?
Most AI startups need five or six pages at launch: homepage, one or two use-case pages, how it works, pricing and a trust page, with about and contact folded in or kept short. A single strong AI landing page is enough if you're pre-launch or testing one buyer.
Six pages fits our website package exactly, and each extra page, such as another use case, is $500. The cost side is covered in detail in AI startup website cost. Grow the site by adding use-case pages as you learn which buyers convert, not by adding generic pages because other startups have them.
