Full Episodes and Show Notes
SmartGateVC – Deep Tech, From Lab to Launch
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Deep tech investing focuses on companies built around fundamental technical breakthroughs rather than incremental software improvements. These businesses tend to emerge from research labs, require longer development cycles, and carry real technical and regulatory risk. The tradeoff is defensibility. If the technology works, it’s difficult to replicate.
I’m joined by Areg Alimian and Ashot Arzumanyan, co-founders and partners at SmartGate VC, to discuss how they approach that tradeoff in practice. SmartGate’s strategy is deliberately positioned ahead of the hype cycle. Rather than pursuing software-only or “AI wrapper” startups, the firm concentrates on physical AI, secure edge infrastructure, and neurotechnology, including brain-computer interfaces with medically grounded use cases and defined regulatory paths.
We discuss how that thesis shapes investment decisions, from early sourcing through follow-on capital, and why security and governance have become gating factors for enterprise AI adoption. Areg draws on his experience as an operator who has built and exited hardware companies and led major product and M&A efforts, while Ashot brings a background in investment advisory, management consulting, and long-term deep-tech investing. The conversation also covers what tends to break when science leaves the lab, how companies are positioned for acquisition, and how technically ambitious ideas are turned into durable businesses.
Episode Highlights:
- [02:57] Areg describes his early career in Silicon Valley, including work on networking systems and foundational Wi-Fi standards.
- [04:41] Ashot explains his transition from economics, consulting, and investment advisory into deep-tech investing.
- [06:57] SmartGate’s strategy of investing ahead of the hype cycle, rather than chasing crowded markets, is outlined.
- [08:21] The distinction between software-based AI and physical AI is discussed, including why real-world deployment changes the risk profile.
- [09:17] Neurotechnology and brain-computer interfaces are discussed as medically grounded opportunities with current market and reimbursement paths.
- [11:14] Why low-barrier “AI wrapper” companies are avoided due to limited defensibility.
- [14:17] The challenge of scaling university-born technology beyond the lab and into cost-effective production is examined.
- [16:26] Broader implications of AI automating junior roles and the downstream effects on workforce development are considered.
- [18:45] Security and governance are identified as major bottlenecks to enterprise adoption of agentic AI.
- [22:23] High-risk neurotechnology investments are discussed, including minimally invasive approaches to accessing and modulating the brain.
- [26:05] Commercial risk is explored through examples in cybersecurity and vulnerability detection across hardware and software systems.
- [27:57] Early markups, fund scaling challenges, and maintaining access as check sizes grow are discussed.
- [32:48] We discuss follow-on vehicle strategy for participating in select pro-rata opportunities.
- [34:26] Lessons from M&A experience are applied to making early-stage companies more attractive acquisition targets.
- [39:08] The idea that science and execution are multiplicative not additive in deep tech is discussed.
- [42:14] Liquidity timelines are examined, including why some cybersecurity and infrastructure investments may generate earlier DPI than neurotechnology.
- [43:48] Secondary liquidity and follow-on interest are discussed as alternative paths when M&A markets slow.
- [48:35] The value of working with founders before a term sheet is explored, including how early collaboration affects valuation and trust.
- [51:52] The risk of sunk-cost bias is addressed, and why time spent with strong founders is not viewed as wasted even when a deal doesn’t proceed.
- [54:50] The Armenian tech diaspora is described as a meaningful sourcing and access advantage.
- [01:02:43] Strategies for helping technically driven founders focus when pursuing too many product paths at once are shared.
- [01:07:12] Reflections on criticism of the firm’s strategy and the decision to remain specialized.
- [01:15:46] The internal decision-making process is explained, including why compromise is avoided.
- [01:17:04] Reflections on failure as a necessary part of building and investing in complex technologies.
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