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10 Best Design Agencies for Agentic UI Patterns - August 2026
Every interface convention we have assumes the user does the work. Agentic products break that contract, and the patterns are still being invented. We checked 10 agencies on five public criteria.
The best design agencies for agentic UI patterns in 2026 are Studio Maydit, Kvalifik, Feels Like, Foundey, basement.studio, Phantom, BX Studio, Lighthouse Digital, Lazarev, and Trueform. Studio Maydit and Foundey lead for teams designing the interface itself rather than the site around it. Lighthouse Digital and Trueform are the wrong fit for this work, because both build marketing sites rather than product interfaces.
Almost every interface convention we use assumes the person is doing the work. You click, something happens, you see the result, you decide what to do next. Loading states, undo, forms, and confirmation dialogs were all designed for that arrangement, where cause and effect sit next to each other in time.
An agent breaks the arrangement. The user starts something and walks away. The system works for four minutes, or forty, touching things the person cannot see. Then a result arrives, and it may be excellent, or subtly wrong in a way that takes longer to check than it would have taken to do the task by hand.
The patterns for this are genuinely not settled yet. Nobody has agreed how to show progress on work that cannot be measured, how to interrupt something already half done, how to present a change for review without making the review harder than the task, or how to ask for permission in the middle of a job without training people to click yes automatically.
That is why this is a design problem rather than an engineering one. The model quality decides whether the output is good. The interface decides whether anyone can tell, and whether they trust it enough to look away. The ten studios below are ranked on how well they handle that second question.
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 one craft their real specialism, 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 teams design an agent interface
Three patterns fail repeatedly, and each one is the easy answer to a hard question.
The text box becomes the entire product. A single input is the fastest thing to build and it always demonstrates well, because the person demonstrating knows what to type. Everyone else does not. A blank field communicates nothing about what the system can do, so each new user has to guess the boundaries by failing, and most give up before they find the good paths. The people who stay develop private habits that never spread through the team. A text box is a fine escape hatch and a poor front door. Put the three jobs people actually want on the surface as real controls, and keep typing for the cases you did not anticipate.
Progress gets faked because real progress cannot be measured. The system genuinely does not know how long it will take, so the interface shows a spinner, or worse, a percentage bar that a developer invented. Then it sits at eighty percent for two minutes and everything you built for trust is gone at once. Users forgive slowness far more readily than they forgive a lie about slowness. Show the work instead of the estimate. A running list of what it is doing right now, in plain language, holds attention through a long wait and doubles as an explanation of how the thing works.
There is no good way to disagree with the result. The output arrives with two buttons: accept or reject. But real work is not binary. The answer is usually mostly right with one wrong assumption, and what the person needs is to correct that part and have the correction stick. Reject sends them back to the beginning to do it themselves, which teaches them the tool costs more than it saves. Design for partial disagreement. Let people edit the result directly, show clearly what was changed and by whom, and make sure a correction today changes behaviour tomorrow.
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 | Teams designing review, interruption, and permission into an agent product |
Maydit is the right call when the interface has to make a long, invisible piece of work legible. Book a 30-minute call.
2. Kvalifik
Kvalifik is a Copenhagen team of 11 to 50, founded in 2015, with Veo, Maersk, and Relesys named, and published AI client work. Veo is the reference that matters here, a computer vision product where the system watches a game and decides what mattered. Designing for software that observes and judges on your behalf is the same trust problem an agent has, arriving through a different door.
They publish no pricing, Webflow rather than product design is their platform, and a Danish team overlaps only with US mornings, which is limiting for the daily back and forth interface work needs.
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 | Teams whose product makes judgements the user has to accept |
3. Feels Like
Feels Like is a Los Angeles studio founded in 2023 building in custom code, with Google, Nike, LVMH, and Suno AI named. Suno AI is the useful reference, a generative product whose output differs on every run, which forces exactly the design questions this article is about. How do you present a result nobody can predict, and how do you help someone judge whether it is any good.
They publish no pricing and no team size, they are a young studio with a short public record, and their strongest published work is brand and marketing rather than long-running product interfaces.
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 | Teams whose output is different every time and hard to evaluate |
4. Foundey
Foundey is a San Francisco studio founded in 2021 with DemandIQ, Traycer, and Sero AI named, and published AI client work. Working in Figma only is the right shape for this particular brief, because agentic interface work is design thinking rather than site building, and their clients are early AI companies rather than established brands adding a feature.
They publish no pricing and no team size, they do not build what they design so you carry the implementation, and a small studio with no public pricing is hard to plan a budget around.
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 with engineers who need design direction on the interface itself |
5. basement.studio
basement.studio works from Mar del Plata and Los Angeles, founded in 2018, a team of 11 to 50 building in custom code, with a published minimum and Vercel, Cursor, ElevenLabs, Harvey AI, and Scale AI named. Cursor and Harvey are two of the clearest examples of agentic products in real use, so this team has watched these patterns being invented rather than reading about them afterwards.
Their published work is mostly marketing sites rather than the product interfaces themselves, they are small relative to demand, and custom code means the engagement includes engineering you may not need.
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 | Teams who want a partner already close to how these products are built |
6. Phantom
Phantom works from London and Auckland, founded in 2013, a team of 51 to 200 building in custom code, with Diageo, SAP, Financial Times, and Zendesk named, plus published AI client work. Zendesk is the relevant one, a product where software suggests and a human decides, thousands of times a day. That specific arrangement, assistance rather than replacement, is where most agent products actually live.
They publish no pricing, a team of that size means layers between you and the designers, and their strongest public work is brand rather than long-running interface systems.
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 | Teams building assistance into a workflow a human still owns |
7. BX Studio
BX Studio is a New York team of 11 to 50 with a published minimum and Reddit, Headspace, ASAPP, and Verifone named, plus published AI client work. ASAPP builds AI assistance for support teams, which means dense professional interfaces where the software proposes and a person under time pressure accepts or corrects. That is a harder design problem than a consumer chat window and much closer to real agent work.
They publish no founding year, and Webflow rather than product design is their platform, so a long interface engagement is not their usual shape.
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 | Teams designing for professionals who accept or correct under pressure |
8. Lighthouse Digital
Lighthouse Digital is a London studio working in Webflow, with a published minimum and HelloSelf, Freetrade, and IGN named. Freetrade is the interesting reference for this brief, a regulated product where the interface has to make consequences clear before someone commits. Making a person understand what they are agreeing to is precisely the problem a permission prompt has.
They publish no AI client work at all, no founding year and no team size, and Webflow means marketing pages, so product interface work is outside what they do.
Check | Finding |
|---|---|
Based in | London, UK |
Founded | Not published |
Team size | Not published |
Primary platform | Webflow |
AI-sector proof | No. No published AI client work |
Named clients | HelloSelf, Freetrade, IGN |
Pricing | Published minimum |
Best fit | Teams whose permission steps must be genuinely understood |
9. Lazarev
Lazarev is a San Francisco team of 51 to 200, founded in 2015, with a published minimum and Payoneer, Peel, Elva, and Mozayix named, plus published AI client work. Their published work is unusually weighted toward complicated product interfaces rather than marketing sites, which makes them one of the more directly relevant studios here for the actual screens.
They are large enough for account layers between you and the designers, their process suits longer engagements than an early team may want, and their strongest references are conventional software rather than agentic products.
Check | Finding |
|---|---|
Based in | San Francisco, USA |
Founded | 2015 |
Team size | 51-200 |
Primary platform | Mixed |
AI-sector proof | Yes. Published AI client work |
Named clients | Payoneer, Peel, Elva, Mozayix |
Pricing | Published minimum |
Best fit | Teams whose interface is dense and needs experienced product designers |
10. Trueform
Trueform is a Swiss studio founded in 2022 working in Framer, with a published minimum and Miro, Morning Brew, Bilt Rewards, and Gather named, plus published AI client work. Miro is worth noting, a product where several people and several processes act on the same canvas at once, which is a useful reference for showing who did what when the answer is sometimes the software.
Framer is a marketing site tool rather than a product design practice, which is the main reason they sit last on this list, they publish no team size, and the time difference slows the daily rhythm interface work depends on.
Check | Finding |
|---|---|
Based in | Wil, Switzerland |
Founded | 2022 |
Team size | Not published |
Primary platform | Framer |
AI-sector proof | Yes. Published AI client work |
Named clients | Miro, Morning Brew, Bilt Rewards, Gather |
Pricing | Published minimum |
Best fit | Teams whose immediate need is the site rather than the interface |
How to choose between them
Sort by which pattern is failing you.
People do not trust the result enough to use it. Studio Maydit or Kvalifik.
Nobody can tell what the system is doing while it works. Feels Like.
Your engineers can build it but nobody is deciding the shape. Foundey.
Professionals use it all day and it slows them down. BX Studio or Lazarev.
One test before signing. Ask them to sketch what your product shows during a four-minute task. A studio that understands this work will ask what it is doing during those minutes and want to name each step for the user. One that draws a loading state and moves on has treated the hardest part of your interface as a gap between screens.
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