01
Keywords with verified volume
The classic layer: search terms with real traffic numbers behind them, pulled from keyword databases and checked against what actually ranks.
Our four-layer SEO and AEO strategy your business needs
Every rank tracker shows you the same thing: keywords with search volume. Your buyers also type phrases no tool reports, ask full questions, and describe their situation to an assistant in three sentences. Our method follows from that gap.
- Bottom of the funnel first: the clusters closest to revenue get built and approved before anything upper funnel, so the earliest content earns pipeline.
- The journey in your language: we map stages the way your buyers actually move, in your vocabulary. If your deals pass through a picking a provider stage, the map says picking a provider.
- Clusters before structure: you approve the clusters first, and only then do we build site structure, information architecture, and storytelling on top of them. Every page inherits its reason to exist from an approved cluster.
- The working scale: around ten clusters, each carrying at least a hundred keywords and a hundred prompts, and grown toward five hundred to a thousand as the engagement matures.
The four layers of a cluster
02
Business keywords with zero volume
Phrases from your own briefs, strategy documents and sales calls. No tool reports volume for them, and they describe exactly what you sell.
03
Long-tail questions
The full questions buyers type, including everything the People also ask boxes reveal. They follow from the first two layers and read the way people actually search.
01
Prompts at three lengths
One sentence, two sentences, a short paragraph. The short ones behave like keywords. The long ones sound like a buyer describing their situation to an assistant.
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Our portfolio encompasses a wide range of digital designs essential for the growth of modern businesses.
Lazarev.agency designs the best UI for AI products. Officially.
Lazarev.agency is more than about making profits for us and our clients. We're committed to saving lives in Ukraine, taking on pro bono projects, championing diversity, equity, and inclusion.
01
$500M+
in funding secured for our clients
02
120+
awards backing our excellence
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2015
founded, 10+ years of experience
04
San Francisco, CA
AI product design agency
05
Full-cycle product design
from user research to production-ready design systems
Among our clients:
Award‑winning product design agency for AI‑native B2B platforms
We’re a UX/UI web design agency with 120+ awards that helps AI‑native and AI‑ambitious B2B teams translate complex products into clear, conversion‑ready websites.
Webby Awards x10
Red Dot Design Award x6
Awwwards x16
FWA x5
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.
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.
At this stage, clients engage us for 4–6+ month AI & data product UX redesign programs, treating us as their primary product design partner for the core platform.
10+ years
of experience in UI/UX design
Trusted by over 1,000 companies of all sizes
120+
international industry awards
600+
projects successfully completed
How our keyword research runs:
01
Seeds from your documents
We generate seed keywords per cluster from your briefs, strategy papers, and sales material.
02
Tool expansion
The seeds go through keyword databases for matching terms, related terms, and volume data, and come back as one consolidated report per cluster.
03
AI filtering
A model scores every term against your company profile and drops what you do not sell, which turns out to be most of the raw list.
04
Competitor matching
We pull the keywords your search competitors and your AI citation competitors already win, and fold in the ones you have a right to contest.
05
Manual cleanup
A human walks the remaining list and cuts it to a few thousand keywords worth ranking for. Your clusters are built from that list and nothing else.
Frequently asked questions
How we work, scale, and deliver measurable outcomes.
Why not go straight for the high-volume keywords?
Because volume measures competition as much as it measures demand. The high-volume head of your category is where every agency sends every client, and outranking that crowd is slow and expensive. The four-layer model wins on the terms your buyers use at decision time, many of which show little or no volume, and takes the contested head terms only where the verdict says the fight is worth having.
What if our category barely has any search volume?
Then a volume-only methodology would tell you search isn't for you, and it would be wrong. New and narrow categories live almost entirely in layers two through four: business keywords from your own documents, long-tail questions, and prompts. Buyers there ask assistants more than they scroll results pages, which makes the prompt layer your biggest asset instead of an afterthought.
Who approves the clusters?
You do. The extended cluster grouping report goes to your team as a strategy argued in plain language, and nothing gets built until you sign off on the clusters. That includes site structure: pages, information architecture and storytelling are all downstream of the approved map, so there is no moment where content appears that nobody agreed to.
What happens after the clusters are approved?
They become the brief for everything downstream. Site structure and page templates get built against them, and the publishing loop in continuous demand generation works through them in the sequence you approved. The clusters are also where measurement attaches, so share of voice gets reported per cluster instead of as one number for the whole site.
Let's talk about your AI adoption challenge