10+ years
of experience
in UI/UX design
in UI/UX design
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B2B web design agency
Become a client
We're a B2B web design agency built around the product itself. B2B users don't trust an AI product by default. They trust it because the interface shows them what the model did, why, and how to push back. At Lazarev.agency, we design the surfaces where AI meets the user: model output, citations, confidence states, fallback behavior, and human override.
- Designed around the product
Every B2B feature has a moment where the user should decide whether to trust what's on screen. We design for those moments: live data, partial states, retries, latency, error recovery, and the explainability surfaces a technical evaluator scrolls through in the second meeting. The product shows up working. - Trust built into the interface
Citations, source linking, confidence indicators, audit trails, governance views, and human-in-the-loop controls live in the UI itself. Users see why the product produced a given output, where the answer came from, and how to correct it. B2B users only return to a product once it earns their trust. We design for the second session, after the first impression has worn off. - Strategic design systems engineered for scale
A reusable library covering navigation, form patterns, data display, output rendering, state, and approval flows — the backbone of every B2B web design engagement we run. Your team extends a coherent system across every feature, so the tenth release ships in the same shape as the first.
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$500M+
in funding secured
for our clients
for our clients
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120+
awards backing
our excellence
our excellence
/ 03
2015
founded, 10+ years
of experience
of experience
/ 04
San Francisco, CA
AI product design agency
/ 05
full-cycle product design
from user research to production-ready design systems
Lazarev.agency designs the best UI for AI products. Officially.
2026 Webby Winner, AI — Visual Design. Three years of Webby recognition for AI product design.
Among our clients:
Awards
& Recognition
& Recognition
Our team’s work was honored with most of the world-known trophies
120+
Awards won all time
CSS Design
Website of the year
Awwwards
Agency of the year nominee
The Webby Awards
The FWA
Awwwards
Red Dot Awards
Behance
the drum awards
Where B2B web design for AI products keeps stalling
Founders and Heads of Product running enterprise B2B sales express the same set of frustrations. The website looks current, but the product behind it feels older. The demo lands and the trial collapses. Users churn at the same point in the flow, and the team rebuilds the same surface every quarter.
Features bolted into UI built for an older product
New functionality dropped into a screen with no place for live data, no state for partial results, no override path. The product returns something useful and the screen has nowhere to put it. Users see a panel pasted over the workflow they came to do — common in AI-native product launches built on top of a legacy app shell.
Generic patterns standing in for product UX
Teams default to a chat panel or a wizard because it's the fastest path to launch. The workflow underneath needs a purpose-built surface: structured inputs, intermediate previews, edit-and-rerun controls, and a place to compare versions. The default pattern becomes a fallback for design work the team didn't get to.
Trust gaps in the interface
Users can't tell why the product returned a given answer. No citations, no confidence signal, no way to flag a bad result. The first product error costs the user's confidence in the whole tool, and they stop using the feature before the team can ship a fix.
Design debt as the product surface grows
Every new feature ships a slightly different input control, output card, and feedback pattern. Six months in, the product feels stitched together, the team spends sprints aligning components, and new surfaces inherit the inconsistency.
How we design B2B products for AI-native teams
Our B2B web design work starts inside the product, where buyers and users meet it. We map what the product does, where it fails, and what the user has to decide at each step, then design the surfaces meeting those decisions. The product ships ready for users who probe edge cases on day one — a discipline we lean on hardest in AI-native product work.
Research grounded in real product behavior
We sit with the product team, read the data, watch users try the feature, and catalog the edge cases. The interaction model comes from how the product behaves, with no generic patterns lifted from competitors.
Interaction design for live workflows
Flows, states, and controls covering the full lifecycle of a task: pre-submit context, in-flight feedback, output rendering, post-output editing, retry, escalation. Every state has a designed surface, including the failure ones.
Production-ready design system
A component library handed to engineering with tokens, variants, and accessibility specs. Your team builds the next ten features on the same foundation without rebuilding primitives.
Implementation partnership and instrumentation
We stay through build, QA the surfaces in production, and help instrument the metrics worth tracking: acceptance rate, override rate, recovery from errors, time to first useful output. Product decisions sit on top of actual usage data.
Case studies
AI products with sites doing real sales work
A B2B AI copilot raising Series B with a demo-led product. A risk platform increasing AI usage after a UX redesign. Enterprise-grade fintech sites engineered to survive procurement on the first pass. Here are case studies of websites running inside the deal cycle.
What we deliver for B2B AI product teams
Why B2B teams pick us for their AI story
Teams come to us when the next round depends on a conversational UX investors trust, when enterprise procurement slows deals down because the site falls apart under technical review, or when sales and product start telling two different AI stories. The recurring note in our debriefs: the website starts pulling weight inside the deal cycle, and the AI claim on the homepage matches what a trial user meets in week one.
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“Through a detailed understanding of the client’s platform, Lazarev. was able to create a clean and intuitive UI/UX design that ticked all the boxes. The team was receptive to all requirements and requests and adapted well to timeline changes. They produced accurate mockups at every iterative stage.”
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“Lazarev. fostered a positive engagement by delivering a navigable site that allowed users to absorb information quickly. The team led a thoughtful, efficient workflow that was always prepared for meetings.”
Industries we know inside AI B2B
Fintech, AI and ML platforms, enterprise SaaS, healthcare, logistics, legal tech, ad/martech, real estate, media and content, Web3 — the industries where B2B buyers run procurement, security review, and a working trial before they sign. We design for the buyer who will run a sandbox before booking the next call.
Who we are and why teams like yours work with us
We exist for B2B teams under pressure to turn an AI roadmap into visible product usage, expansion, and a safer story in front of the C‑suite and investors. If design isn’t moving revenue, adoption, or retention, it’s decoration. We design to avoid that. Since 2015, we’ve shipped 600+ products and earned 120+ awards for work on complex, data-heavy tools: fintech platforms, AI copilots, decision engines, and vertical SaaS. Our work has helped clients turn “we have AI features” into “our customers actually use and pay for them.”
We started designing AI products in 2017, long before “AI-native” became a buzzword. With 30+ AI products shipped, we focus on the hard part most teams struggle with: making complex intelligence feel simple, trustworthy, and obviously valuable in a demo, a POC, or a QBR. We’re a 40+ person team of UX strategists, product designers, and analysts who treat design as a business function. Every engagement is anchored to the metrics you care about: AI feature adoption, activation and retention in key accounts, time-to-decision in core workflows, and upgrade/expansion tied to AI-powered plans.
120+
international
industry awards
industry awards
/ 02
600+
projects
successfully completed
successfully completed
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We operate on a simple principle: if you're not measuring design against business outcomes, you're wasting money.
What sets us apart from a typical agency or a single in-house hire is pattern recognition at scale. We’ve seen what works – and what quietly kills adoption – across hundreds of AI and data-heavy products. That lets us spot failure modes early, bring proven interaction patterns to your team, and reduce the risk that your next AI release is another unused toggle in a settings menu.
We start with research not because it’s “best practice,” but because designing without understanding your users, your market, and your revenue model is just guessing with nicer pixels. From there, we collaborate with your product, AI, and design leaders to define where AI should show up, how it should behave, and how to make it obvious, safe, and monetizable.
If you’re a Head of AI, Product, or an AI-native founder who needs AI capabilities to be seen, understood, and used now, not someday, we’re built to be that partner.
How a B2B AI product engagement runs
A predictable rhythm covers product UX, product surfaces, and demo flows inside the same 4–8 month engagement. We start with how a B2B buyer evaluates an AI product, then design the surfaces meeting that buyer where the deal closes — inside procurement, inside a sandbox, inside the second meeting.
The deck closes the meeting. The product closes the deal.
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Discovery and product-behavior mapping
Stakeholder sessions across Product, Engineering, Design, and Support. We pull usage data, observe users, and catalog product behavior across success, edge, and failure modes. Scope locks once we know what the product actually does.
02
Interaction architecture
One model of how a user works with the product: inputs, outputs, controls, states, and recovery. Decisions land here, before any screen mockups begin. The team agrees on behavior before we move pixels.
03
Design system and core flows
Components, tokens, patterns, and the primary flows built in parallel. Engineering gets a working system early, so new features land in the product on the same release cadence.
04
Launch, instrumentation, and iteration
We stay through the ship, QA the surfaces under real load, and help the team set up the metrics worth watching. The first iteration starts before the launch press cycle ends.
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FAQ
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How is Lazarev.agency different from other B2B web design agencies?
Most B2B web design agencies stop at the homepage. We keep going into the product, the workflows, and the design system your engineering team builds against. Deliverables are interaction models, production-ready components, and a system covering everything from onboarding through advanced use.
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How fast can we go from kickoff to a demo investors and B2B buyers trust?
For a founder shipping a near-term round, 3–4 months gets a working demo with the AI UX investors evaluate. The full 4–8 month engagement covers product UX, product surfaces, and demo flows, so the website carries the same AI claim the demo backs and the product delivers in the trial.
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What does a B2B AI product design engagement cost?
Engagement size depends on complexity, scope, pod size, and timeline. After a structured intake and audit, you get a concrete estimate.
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Do you work on AI-native product UX?
Yes. AI-native product work is a recurring specialty for us, with engagements covering model output surfaces, trust patterns, agent flows, and the design system holding it all together.
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Can you work with our existing brand and design system?
Yes. We extend the system your team already uses, follow your naming conventions, and contribute new components into your existing library. The engagement deepens what you have without forcing a rebuild.
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