Erez Perlmuter

The 5 biggest mistakes Israeli founders make when scaling to the U.S. (and what to do instead): At a recent Google for Startups event, Yasmin Lukatz, Founder of ICON - Israel Collaboration Network, shared some truly golden lessons from working with Israeli entrepreneurs entering the U.S. market. Here are the 5 most common mistakes to avoid, according to Yasmin: 1. Building for the wrong market Too many founders validate only in Israel, then discover too late that their product does not fit U.S. customers. The fix: Before writing a single line of code, speak with 10-20 U.S. customers to validate the problem and solution. 2. Misreading cultural signals American politeness often hides rejection. ↳ “It’s interesting” usually means “I’m not interested.” ↳ “Let’s do lunch” without a calendar invite will not happen. The best way to reach an investor is through another founder they already back, using a concise “forwardable email.” 3. Overemphasizing the idea, underemphasizing the team Investors care more about resilience and adaptability than the initial idea. The fix: Highlight your team’s strength, your ability to pivot, and your long-term mindset. 4. Underestimating the GenAI paradox AI lowers the cost of building and speeds up time to market, but that pace creates more pressure on teams. The fix: Focus on mental toughness, resilience, and team balance. Technology can speed the race, but people carry it. 5. Neglecting community Founders often underestimate the power of networks built on trust and reciprocity. The fix: Don’t just network for yourself. Contribute to others. Over time, a culture of giving becomes your most valuable asset. The truth is, startups rarely fail because of technology. They fail because founders misread markets, culture, or people. Avoiding these five mistakes can make all the difference. Which of these do you see most often among founders expanding abroad?

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Tech continues to drive Israel’s economic resilience, but beneath the surface the ecosystem is showing signs of strain and health tech is feeling the pressure most. The announcement of clinical AI company Aidoc's recent $150 million raise, backed by General Catalyst, Square Peg, nVentures (NVIDIA’s venture capital arm), and four major U.S. health systems, is a sign of what is still possible: when the science is solid, the platform is ready, and the value is global, capital will follow. This is proven by the over 45 million patients currently benefitting from Aidoc's integration across more than 150 health systems. Aidoc’s success is an outlier today, but it should be the model. As the largest sector in Israeli innovation, with over 1,600 companies, health tech should be a source of strength. Instead, in the first half of 2025, it drew just $630 million in private funding — the lowest total in five years. Median deal sizes are shrinking, and time from seed to Series A has stretched to 54 months, pointing to deep structural challenges rather than a short-term slowdown. Capital is flowing elsewhere, toward sectors with faster cycles and clearer paths to scale. Cybersecurity raised $2.2 billion with a median round size of $25 million in H1 2025, while business software led all sectors with $3.2 billion. Health tech is struggling to compete for attention, investment, and talent. These trends are part of a broader shift. Israel’s global innovation position is narrowing, infrastructure hasn’t kept pace with the needs of deep tech, and overreliance on a few sectors is leaving others under-supported. Talent shortages and limited access to global markets are compounding the pressure. At Startup Nation Central, we are seeing this firsthand. Through our work with the 8400 The Health Network Health Network and across the ecosystem, the signals are clear. Health tech is underfunded and underprioritized at a time when its relevance has never been greater. Still, the fundamentals are here. Israel has a strong scientific foundation, a deep pool of entrepreneurial talent, a world-class healthcare system, and health professionals with a track record of innovation. Add to that a growing global demand for health solutions, and the potential is clear. With targeted investment, a renewed focus on translational research, and the right strategic partnerships, health tech can not only recover but take the lead as Aidoc has. The opportunity is real and so is the urgency to act on it. 

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Ever since Eyal Melamed joined as our VP R&D, we've been having some incredible, thought-provoking conversations. These aren't your typical executive check-ins. We get into the weeds on the technical challenges that fascinate us both - the kind of deep infrastructure work that brought Eyal to Rise in the first place. We talk about what it truly takes to make AI work at scale in ad tech - a massive undertaking that spans tackling infrastructure challenges, processing hundreds of trillions of data points in real-time, and building auction systems that simply never fail. Eyal calls our Smart Auction Management technology "one of the most sophisticated AI-powered auction engines in the industry." Coming from someone who’s seen and navigated scale at some of the most advanced tech organizations, that hits differently. This piece came out today about his take on what we've built here. https://lnkd.in/dbuSK2Nd Honestly, during all these conversations, one thing became clear to me: we’ve spent so much time building that we haven’t shared how we actually think differently about AI infrastructure. We’re built on a foundation of big data expertise - processing hundreds of trillions of data points every single day (take a moment to let that sink in..). We’ve engineered AI-based autoscaling that maintains performance at millions of requests per second. Our optimization models don’t hide behind black-box magic - they deliver transparent, explainable results.  And now, we’re layering Gen-AI on top of an infrastructure that already runs at scale like few others can imagine. So something this big calls for something new: Every week, I'll be sharing insights from our journey building AI-driven programmatic technology - the technical and strategic thinking behind systems that actually work in production. Excited to share the lessons we're learning while building AI at scale. P.S. Curious what you see here — authentic photo or AI-generated?

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