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10 Best Custom Code Website Development Agencies for LLM Platforms - August 2026
An LLM platform is evaluated by an engineer with a terminal open, not by a buyer reading a page. We checked 10 custom code agencies on five public criteria.
The best custom code website development agencies for LLM platforms in 2026 are Studio Maydit, basement.studio, Feels Like, Phantom, Engine Digital, Foundey, BX Studio, Kvalifik, and Flow Ninja, with Feely Studio also worth a look. Studio Maydit and basement.studio lead for platforms whose first user is an engineer with a terminal open. Engine Digital and Kvalifik are the wrong fit unless your buyer is procurement rather than a developer.
Nobody reads your homepage. They scroll it looking for the code block, and if there isn't one they open your docs and never come back.
That is the entire behaviour pattern for an LLM platform, and it is why marketing sites in this category fail differently from every other kind of site. Your evaluator is not weighing benefits. They are trying to establish, in about two minutes, three facts: what models you have, what it costs to run a request, and whether they can get a response back before their coffee gets cold. Everything else on the page is an obstacle between them and those answers.
This is also the rare category where the audience can check every claim you make, immediately, for free. Say you are fast and they will time it. Say you are cheaper and they will do the arithmetic against the provider they already use. Say you are simple and they will paste your example into a terminal and see whether it runs. A page written in the usual persuasive register does not just fail to convince this reader. It marks the company as one that does not employ people like them.
The other half of the problem is that your site is not the only surface. Docs, status page, changelog, and playground all carry more weight than the homepage, and they are usually built by different people at different times with no shared system. That fracture is what separates these ten agencies.
How we picked these agencies
This is a teardown, not a directory listing. For each agency we read their own site and their public record, then checked five things you can verify yourself in an afternoon:
Platform depth. Is custom code their main craft, or one line on a long service menu?
AI-sector proof. Named AI clients and published work, or just the word "AI" in the copy?
Pricing. Do they publish a minimum at all, or keep it behind a call?
Team shape. Who actually does the work, and how many clients are they carrying at once?
Their own site. Distinctive, or the same template as everyone else on this list?
That last one gets skipped most often. An agency's own website is the only project where nobody overruled them. No client committee, no inherited brand book. If their own site is forgettable, you have found their ceiling.
Every fact below comes from the agency's own site or a public listing. Where a number is not public, we say so rather than guessing.
What goes wrong when your reader can verify everything
Three failures are close to universal on LLM platform sites, and each one assumes an audience that will take your word for something.
The marketing site and the docs behave like two different companies. They use different navigation, different typography, sometimes different names for the same concept, and moving between them feels like leaving one product for another. Engineers spend nearly all their time in the docs, so the docs are your real front page and the marketing site is the thing they pass through once. Treating them as one continuous surface, with shared components and consistent language for models, tokens, and limits, does more for conversion than any hero section. The version of this that hurts most is a term that means one thing in the marketing copy and something slightly different in the reference, because the reader assumes the error is theirs and loses confidence in both.
There is nothing to run. The page describes capability instead of demonstrating it, so the reader has to sign up before learning anything. That order is backwards for this audience. What works is a request they can copy and execute against a real endpoint without an account, a response they can see arriving, and an honest note about what the free path does not include. The distance between landing on the page and seeing your system return something should be measured in seconds. Every step you put in front of that costs you a proportion of the exact people you most want, and they will not tell you they left.
The numbers on the page go stale and get caught. Model names, context limits, rate limits, and per-token pricing all change frequently, and on most sites they are typed into a design tool as copy, so they drift from the docs within weeks. This reader checks. When the homepage claims a context window the reference contradicts, they do not send a correction, they conclude your organisation is careless and take that impression into the trial. Anything factual on a page like this needs to come from the same source the docs use, so it cannot fall out of date on its own. That is an engineering decision made during the website build, which is why the build matters as much as the design here.
1. Studio Maydit: A Top-Rated Design Agency for AI Founders
Studio Maydit is a web and product design studio working with AI founders in the US, UK, and Europe. The studio builds websites in Framer, Webflow, and custom code, and continues into product design after the site ships.
The clearest outcome is Dualite, where design work supporting a repositioned ICP helped the product reach 100,000+ users in seven months. Recent clients include Wave, PixelFlow, Mi-VAD, and 15 other AI and SaaS teams.
Websites can be bought two ways. Fixed scope runs three to four weeks and suits teams with a launch date. Teams that keep shipping take a monthly retainer instead, covering new pages, campaigns, and product design, with no long lock-in. Fixed-scope projects end with a diagnosis of what is leaking in the product, not a handoff and goodbye.
Check | Finding |
|---|---|
Based in | Remote, serving US / UK / EU |
Platform depth | Framer, Webflow, and custom code |
AI-sector proof | Yes. AI-native clients, published outcome on Dualite |
Pricing | Fixed scope or monthly retainer, quoted per project |
Team shape | Founder-led, small senior team |
Best fit | Platforms whose site, docs, and playground should feel like one product |
Maydit is the right call if the marketing site and the docs currently look like two companies. Book a 30-minute call.
2. basement.studio
basement.studio is an 11 to 50 team across Argentina and Los Angeles with a published minimum and Vercel, Cursor, ElevenLabs, Harvey AI, and Scale AI named. That is the strongest developer-platform roster available here by a wide margin. Vercel in particular is the closest thing to your brief, a technical product whose marketing site has to satisfy engineers without becoming documentation.
They are a small team for the size of some of these projects, their aesthetic runs bold in ways a conservative enterprise buyer may resist, and demand at that reputation means availability is not guaranteed.
Check | Finding |
|---|---|
Based in | Mar del Plata, Argentina and Los Angeles, USA |
Founded | 2018 |
Team size | 11-50 |
Primary platform | Custom code |
AI-sector proof | Yes. Published AI client work |
Named clients | Vercel, Cursor, ElevenLabs, Harvey AI, Scale AI |
Pricing | Published minimum |
Best fit | Platforms selling to engineers who judge the site as a product |
3. Feels Like
Feels Like is a Los Angeles studio founded in 2023 with published AI client work and Suno AI named alongside Google and Nike. Suno matters here because it is a product where visitors expect to try the real thing on the page rather than read about it. That instinct is exactly what an LLM platform needs, and it is uncommon among studios whose work is mostly presentation.
They publish no pricing and no team size, they are new enough that the record is short, and a documentation system is a different scale of work from a marketing site.
Check | Finding |
|---|---|
Based in | Los Angeles, USA |
Founded | 2023 |
Team size | Not published |
Primary platform | Custom code |
AI-sector proof | Yes. Published AI client work |
Named clients | Google, Nike, LVMH, Suno AI |
Pricing | Not published |
Best fit | Platforms who need a working playground on the homepage |
4. Phantom
Phantom is a 51 to 200 team across London and Auckland with published AI client work and SAP, Zendesk, and the Financial Times named. SAP is the relevant reference for a platform moving upmarket, where the same site has to satisfy an engineer running a test and a procurement team asking about uptime commitments and data handling.
They publish no pricing, their scale suits enterprises rather than early platforms, and a large studio will move slower than a team shipping model updates every few weeks.
Check | Finding |
|---|---|
Based in | London, UK and Auckland, NZ |
Founded | 2013 |
Team size | 51-200 |
Primary platform | Custom code |
AI-sector proof | Yes. Published AI client work |
Named clients | Diageo, SAP, Financial Times, Zendesk |
Pricing | Not published |
Best fit | Platforms whose site must satisfy engineers and procurement |
5. Engine Digital
Engine Digital has been working since 2002 out of Vancouver and New York, with Autodesk, Goldman Sachs, and HP named. Goldman Sachs is the signal worth reading: if your platform is being evaluated by a bank or an insurer, the questions arrive in a fixed order and a studio used to those clients will have built the compliance and security pages before you ask.
They publish neither pricing nor team size, their AI-sector proof is partial, and their engagement scale and pace suit established companies rather than fast-moving platforms.
Check | Finding |
|---|---|
Based in | Vancouver and New York |
Founded | 2002 |
Team size | Not published |
Primary platform | Custom code |
AI-sector proof | Partial. Enterprise and SaaS clients, no AI case study |
Named clients | Adidas, Autodesk, Goldman Sachs, HP |
Pricing | Not published |
Best fit | Platforms selling into banks, insurers, and public institutions |
6. Foundey
Foundey is a San Francisco studio founded in 2021 with published AI client work and DemandIQ, Traycer, and Sero AI named. Traycer is a developer tool, which means they have designed for people who spot a fake example instantly. If your engineering team wants to own the build and only needs the thinking, this is a sensible shape of engagement.
They are Figma-only, so every line of the site falls to your engineers, they publish neither pricing nor team size, and their clients are early enough that none of the work has been tested at platform scale.
Check | Finding |
|---|---|
Based in | San Francisco, USA |
Founded | 2021 |
Team size | Not published |
Primary platform | Figma-only |
AI-sector proof | Yes. Published AI client work |
Named clients | DemandIQ, Traycer, Sero AI |
Pricing | Not published |
Best fit | Teams whose engineers will build the site themselves |
7. BX Studio
BX Studio is a New York team of 11 to 50 with published AI client work, a published minimum, and Reddit, Headspace, and ASAPP named. ASAPP is a conversational AI company, so they have already worked through how much of a model's behaviour to expose on a public page. Published pricing also removes a round of negotiation.
Webflow rather than custom code is their stated platform, which is a genuine mismatch for a site that needs live code execution, and they publish no founding year.
Check | Finding |
|---|---|
Based in | New York, USA |
Founded | Not published |
Team size | 11-50 |
Primary platform | Webflow |
AI-sector proof | Yes. Published AI client work |
Named clients | Reddit, Headspace, ASAPP, Verifone |
Pricing | Published minimum |
Best fit | Platforms whose public site is mostly narrative, not interactive |
8. Kvalifik
Kvalifik is a Copenhagen team of 11 to 50 working since 2015, with published AI client work and Veo and Maersk named. For a platform selling into European industry, a Nordic studio with a Maersk-scale delivery behind it reads as a safe choice to a buyer who has never heard of you.
They publish no pricing, Webflow rather than custom code is their craft, their client record is short, and Copenhagen hours give a US engineering team limited overlap.
Check | Finding |
|---|---|
Based in | Copenhagen, Denmark |
Founded | 2015 |
Team size | 11-50 |
Primary platform | Webflow |
AI-sector proof | Yes. Published AI client work |
Named clients | Veo, Maersk, Relesys |
Pricing | Not published |
Best fit | Platforms selling into European industrial buyers |
9. Feely Studio
Feely Studio is a distributed European team of 1 to 10 with published AI client work and a published minimum. At that size the person who understands your rate limits is the person writing the page about them, which is the main reason technical copy on this kind of site ends up accurate rather than approximate.
They are very small, so a site plus a documentation system will exceed their capacity, and their published work leans toward marketing pages rather than interactive technical surfaces.
Check | Finding |
|---|---|
Based in | Distributed, Europe |
Founded | Not published |
Team size | 1-10 |
Primary platform | Mixed |
AI-sector proof | Yes. Published AI client work |
Named clients | Noxus, Mutiny, Luasai, Basic Capital |
Pricing | Published minimum |
Best fit | Small platforms who need the technical copy to be exactly right |
10. Flow Ninja
Flow Ninja is a Belgrade team of 11 to 50 working since 2018. The practical case is capacity at a lower rate with European hours, which suits a platform that needs a steady stream of model announcement pages and changelog updates rather than one flagship build.
They publish no client names and no pricing, their AI-sector proof is partial, and Webflow rather than custom code is the craft, so anything requiring live execution sits outside what they do.
Check | Finding |
|---|---|
Based in | Belgrade, Serbia |
Founded | 2018 |
Team size | 11-50 |
Primary platform | Webflow |
AI-sector proof | Partial. Enterprise and SaaS clients, no AI case study |
Named clients | Not published |
Pricing | Not published |
Best fit | Platforms needing steady page output rather than one flagship build |
How to choose between them
Sort by which surface is losing you developers.
The homepage has nothing an engineer can run. Studio Maydit or Feels Like.
Docs and marketing site feel like different companies. basement.studio.
Enterprise buyers arrive with a security questionnaire. Phantom or Engine Digital.
Your model and pricing pages keep going stale. Studio Maydit or Foundey.
One test before signing. Ask how they would keep the model list on the homepage in step with the API reference. An agency that belongs on this brief will talk about pulling from one source so the page cannot drift, and will ask who owns that source today. An agency that says they will update it when you send changes has just described the exact process that produces a homepage contradicting your own documentation within a month.
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