Lusha is the B2B data and intelligence layer for GTM teams and AI agents. It delivers verified contact and company data, enriched with buying signals and shaped by what works for your business. Pulse 2.0 interviewed Lusha co-founder and CEO Yoni Tserruya to learn more.
Yoni Tserruya’s Background
Could you tell me more about your background? Tserruya said:
“I’m a builder at heart, which is still how I think about my job today.I was always a curious kid, more into tinkering than following plans. I started to code when I studied computer science and began my career as an iOS developer at AT&T.”
“Lusha started as a side project in 2016 with my co-founder Assaf Eisenstein, two builders trying to make it easier for people to connect in a professional context. 10 years later, we’ve gone from bootstrapping to a GTM deep intelligence solution, still guided by the same instinct: build something people need and keep learning while you do it.”
Formation Of The Company
How did the idea for the company come together? Tserruya shared:
“It started with a simple problem: connecting with the right people was harder than it should be. Assaf and I saw an opportunity to help business professionals find each other. We originally thought it would be useful for recruiters. But very quickly, salespeople came to the product and found a lot of value in it. Within months of launching Lusha as a Chrome extension, it went viral organically with no marketing budget. That validated that people didn’t just need more data, they needed better data. If your data is wrong, every insight, every action, every decision downstream is wrong too. That became the foundation of everything we’ve built since, and it’s even more important now with AI, agents, and automation.”
Favorite Memory
What has been your favorite memory working for the company so far? Tserruya reflected:
“The moments I value most are when I see the team figure something out that nobody else has figured out yet. When we started building the Deep Intel layer, the part that actually learns your business, not just the market, there was a period where we weren’t sure it would work the way we imagined. A lot of companies talk about personalization but end up delivering a slightly filtered version of the same generic list. Watching our team crack the scoring and recommendation engine, seeing its surface leads that actually made sense for specific customers, in a way you could explain and verify—that was a real moment. It’s the kind of thing that only happens when you have the best technology and the most talented data professionals who really care about the problem they’re solving.”
Core Products
What are the company’s core products and features? Tserruya explained:
“Lusha is accessible across three surfaces. Lusha Workspace is where teams prospect, build lists, and run AI-powered workflows. The browser extension sits on top of LinkedIn and other sites so reps can pull verified contact data without leaving their workflow. And the API and MCP make all of Lusha’s data and deep intelligence available to developers and AI agents.”
“Our data includes verified contact and company data, real-time signals like job changes and department growth, AI-powered lead recommendations that refresh daily based on your ICP, and CRM integration so everything syncs back to where your team already works. We’ve also built ICP Hub, which lets you define your ideal customer profile in plain language and share it across the whole team—so a rep who joined last week is working from the same targeting strategy as your most experienced AE.”
“The whole product is designed around one idea: give GTM teams the right data at the right moment, with the context already attached, so they don’t waste time doing manual work.”
Two-Layer Approach To GTM Intelligence
How do you describe Lusha’s two-layer approach to GTM intelligence and execution? Tserruya described:
“Our tagline is ‘Data You Can Build On,’ and the two-layer architecture is what that means in practice.”
“The Search layer is universal, the world’s most comprehensive, verified, and compliant B2B dataset. Contacts, companies, real-time signals, and market triggers. Fast, accurate, objective. Any company can access this kind of data. What matters is whether yours is the most complete and the most trustworthy. That’s what we’ve built.”
“The Deep Intel layer is different. It doesn’t just know the market; it knows your business. It builds context across four dimensions: your audience, your integrated systems, your usage patterns, and real-time buying signals. It surfaces your highest-value leads at any given moment, scores and prioritizes every opportunity by fit and signal strength simultaneously, and adapts in real time as your strategy evolves. You give it the narrative. You control what it learns. It keeps getting smarter.”
“The Search layer is your foundation. The Deep Intel layer is your edge. Together, they’re the verified, contextual data beneath every CRM, every workflow, every agent.”
Challenges Faced
Have you faced any challenges in GTM/sales recently — and how did you overcome those challenges? Tserruya acknowledged:
“The biggest challenge right now is something the whole industry is dealing with. AI is moving so fast that GTM teams are deploying agents before the data infrastructure underneath them is ready. Agents are only as good as the data they run on. We’ve seen this play out internally and with customers. That’s shaped a lot of our product decisions over the past year: making our data accessible via API and MCP, so that whatever stack a team is using, Lusha can serve as the intelligence layer underneath it.”
Evolution Of The Company’s Technology 
How has the company’s technology evolved since launching? Tserruya noted:
“We started as a browser extension that surfaced contact data. That was the right place to begin — simple, valuable, immediate. Over time, we built out the full platform: enrichment, CRM integrations, search, and filtering. The bigger shift came when we decided to build the Deep Intel layer. That meant investing seriously in machine learning—lookalike engines, recommendation engines, scoring models that learn from your business. We’ve improved our lookalike accuracy by 50% recently. And the next layer is what we’ve just started: making all of this accessible to AI agents through MCP and API, so that autonomous workflows can tap into Lusha data the same way a human would. That’s a fundamentally different architecture than where we started.”
Significant Milestones
What have been some of the company’s most significant milestones? Tserruya cited:
“A few stand out. Getting to profitability while bootstrapped was a big one, it meant we proved the model before we raised. Reaching 1 million users was meaningful because it was organic. And recently, sharing our data with the world – in Claude, ChatGPT, Clay, and the launch of our MCP integration, which means AI agents can now call Lusha data. That one felt like crossing a threshold into a new era of what this company is building toward.”
Customer Success Stories
Can you share any specific customer success stories? Tserruya highlighted:
“One thing I hear consistently from customers is about time. A RevOps lead at a scaling SDR team told our team recently that her reps were pulling 5,000 ICP-fit contacts and blasting them cold — low connect rates, burned contacts, demoralized reps. After moving to signal-based workflows through our API, they shifted to small, precise lists where every lead has a reason behind it. Job change, department growth, intent signals. The connect rates went up because reps were reaching people at the right moment with the right context.”
Revenue
Are you able to discuss revenue metrics? Tserruya revealed:
“We don’t share specific revenue figures publicly. What I can say is the business is healthy. We’ve been profitable, we’re growing, and we haven’t needed to optimize for fundraising headlines over building a real business. That independence has let us make product decisions based on what customers actually need.”
Total Addressable Market (TAM)
What total addressable market (TAM) size is the company pursuing? Tserruya assessed:
“The B2B data and sales intelligence market is large—commonly cited in the multi-billion dollar range, but I think the more interesting framing is what’s happening to the TAM itself. As AI agents become a real part of how companies operate, the need for verified, structured, agent-ready B2B data grows significantly. Every agent doing any kind of outbound or account research is a potential Lusha customer. That expands the addressable market well beyond traditional sales tools.”
Future Of Agentic Enterprise
How do you see the future of the agentic enterprise evolving over the next 1-2 years? What will be most crucial for success? Tserruya predicts:
“The AI pilot phase is over. Companies that were experimenting are now deploying agents to do actual work. The teams that will win are the ones that build their agentic GTM on a solid data foundation. An agent with bad data is worse than a human with bad data; it scales the mistakes.”
“The most crucial thing for success in the next 1-2 years is getting the data layer right. That means verified data, real-time signals, and a system that understands your specific business context — not just generic market data. Companies that sort that out early will build a structural advantage. Not a quarterly edge. A permanent one.”
Differentiation From The Competition
What differentiates Lusha from its competition? Tserruya affirmed:
“First, data quality. We’ve invested heavily in accuracy, freshness, and compliance. That’s not glamorous to talk about, but it’s the foundation everything else sits on.”
“Second, the Deep Intel layer. Most competitors are in the Search layer business; they give you just data. We give you data plus a system that learns your business and tells you where to focus. That’s a different product category.”
“Third, how we’ve built for the agentic era. Our MCP integration means AI agents can access Lusha data natively, the same way they access any tool in their stack. Most of our competitors haven’t gotten there yet.”
“And fourth, compliance. Lusha built GDPR, CCPA, and ISO 27701 in, and we feel good about it. In a world where enterprise buyers are increasingly scrutinizing data practices, that’s a moat that took years to build and can’t be copied quickly.”
Future Company Goals
What are some of Lusha’s future goals? Tserruya concluded:
“The north star is becoming the B2B intelligence layer that every business runs on. The verified, contextual data beneath every CRM, every workflow, every agent.”
“More specifically: we want to be the default data and intelligence layer for AI agents doing GTM work. That means deeper integrations so Lusha is accessible wherever agents are operating It means continuing to make the Deep Intel layer smarter with each use. We want to reach a point where a seller can ask “Who do I need to talk to today?” and get an answer they can trust and act on immediately.”
