Rahul Meka is a venture investor at Playground Global, an early-stage deep tech venture capital firm investing in technical founders to transform ambitious ideas into high-impact businesses.
Who are you and what do you do?
My name is Rahul Meka. I’m an investor at Playground Global, an earlystage deep tech venture capital firm based in Palo Alto. We manage about $1.2 billion and are currently on our third fund. We invest purely in deep tech spanning three main verticals. The first is next-gen compute. That includes everything from the foundations of computation, like EUV lithography, new compute architectures – all the way to applications built on top of computation.
The second big area is engineered biology. We focus on companies using computational biology to build platform therapeutics. These can serve various targets and implement different modalities, all aimed at producing best-in-class drugs. The third pillar is industrial transformation. That’s a bit of a catch-all, but it focuses on how technology – computation, AI and automation can revolutionize legacy industries.
As for my background, I’m a mechanical engineer by training. I started in automotive and was part of the first wave of self-driving. I learned early on that self-driving was at least 10 years away and that prediction turned out to be right. I took those lessons and applied them to a more constrained operational design space in manufacturing, which led me to industrial robotics. Along the way I got exposed to investing. I worked closely with early stage startups solving big problems in self-driving, electrification, mobility and robotics. I taught myself about sensing, planning, computation, and the systems built on top of that.
Along the way, I also got an MBA focused on finance to round out my engineering background. After that, I wanted some startup operating experience and had the opportunity to join a startup I had helped fund. That company was acquired twice in nine months. The final acquisition was by Intrinsic – spin out from Google X, where I spent a year before joining Playground. Now, I spend most of my time thinking about how legacy industries will be transformed. I like system engineering problems that if solved give you compounding economic benefit. The overlap of those two areas is where I like to work. Deep tech is a natural fit.
A weekly dispatch featuring exclusive interviews with deep tech founders & a roundup of the most important deep tech news.
Tell us about your investment strategy. Are there specific industries in deep tech that you focus on?
We invest from pre-seed through Series A. Our strategy is distinct because the investment team is supported by a broader operating platform. Everyone on the investment team is either an engineer or has a P.h.D. By training, they’re scientists or engineers. By experience, they’ve either been entrepreneurs or worked in operating roles. That’s true for the general partners and it’s true for the rest of the team, including me.
Our check sizes range from $3 million to $15 million. We only lead and we always take a board seat. That’s because we’re set up to be very hands-on. We have a 70,000 square foot facility with a machine shop, instrumentation lab, and wet lab. These are the kinds of tools deep tech companies need to go from zero to ten. We want to be involved throughout that journey.
We also have operating support in areas like fundraising, talent acquisition, marketing, design, supply chain, and engineering. All of this exists to help our companies scale while they are still building out their internal teams. Our strategy is built around being early and being useful. We are focused on helping companies build. And we have a clear thesis. We only underwrite technical risk. We do not underwrite market risk.
Our tagline is that we invest between improbable and impossible. These are bets where, if they work, they could have a huge impact on civilization and the economy. That’s how we justify investing in fundamental science and deep engineering problems. Our team is built to evaluate and support that kind of risk.
In terms of sectors, we talked earlier about the three big ones. Personally, I care a lot about legacy industries that haven’t changed in 20 or 30 years. These are industries that can be transformed by electrification, automation, or AI. We’re not looking for incremental improvements. We want step changes.
Have you always been focused on deep tech?
We started with a focus on hardware. That was core from the beginning. The genesis of the firm ties back to Android, so there was always an interest in building physical systems. In Fund I, that focus on hardware led us towards more B2C bets. Computation and automation were still the core pillars of the thesis. This led us to invest in PsiQuantum – which we believe will be the category defining quantum computing company, Velo3D, a metal 3D printing company which we exited, NVision, a quantum sensing company to enhance MRI and Nervana Systems – the first AI accelerator company.
We’ve always been around hardware, but early on the strategy leaned towards consumers. Over time, we realized we’re not great at underwriting market risk. And in B2C, the best tech doesn’t always win. You need the best go-to-market motion, the right brand, the right distribution. Companies like Apple show how much that matters. But the signal we got from the fund was that in B2B and enterprise – technology matters more. It’s more of a technical sale to a sophisticated customer base. You have fewer customers. It’s less about marketing and more about performance. If the system works and is executed well, it will generate value. That model fits our strengths better.
Are there specific geographies you focus on?
We go where the best science and engineering happens. That’s global. We have companies in Canada, Israel, and across Europe in places like Germany and Italy. We also have one in Australia.
But in general, we are agnostic to geography. Local markets are often not big enough on their own. That said, there are some technologies that need to be tailored to specific geographies. We believe the best technology can come from anywhere and serve the world. We follow the science and the people not the location.
Since you’re doing this at such an early stage, how do you go about underwriting technical risk?
We pride ourselves on technical diligence. We approach everything from first principles. We read peer-reviewed papers. We review patents. We try to understand every element of what needs to work and where the risks are.
When it’s brand-new science, it often comes from someone’s dissertation or life’s work. We’re not trying to teach them anything about the science. But we go deep. If we need to, we’ll speak to outside experts. We also have a strong internal bench that can do a first pass and check that something doesn’t violate fundamental physics or chemistry.
Once we get past that first filter, we’ll bring in more specific expertise. One thing that helps is our network. We have a large group of Playground companies. Many of them have cross-domain experts or deep specialists in one area. We also have startups in the building that we haven’t invested in yet. They’re often experts too. So we rely on that community. They help us figure out whether something makes sense. And from there, we get to a point of convergence. That’s when we start to see whether it can actually work or not.
What stands out as critical to building a successful deep tech startup?
It’s about retiring different types of risk. Building a startup for me is really about staged risk underwriting. That’s how I think about it. You don’t want to take on market risk and technical risk at the same time. You want to focus on solving one thing. We work with companies that are taking on deep technical risk. We look for clear articulation of how to get from where you are to where you want to be. If you’re trying to build a million-qubit quantum computer, how do you make the first gate work? What components are needed to get to a million qubits? Break it down into subsystems. Execute toward the milestones that bring those subsystems together. It’s about system integration and making each layer work.
It’s the same for something like long-duration energy storage. You might start at the kilowatt scale. Then you ask what it takes to move to gigawatt scale. What subsystems need to be built? What steps need to happen in between? Founders need a clear understanding of the capital it takes to do that. And they need to communicate that clearly to investors who will underwrite the company later.
The founding team has to be technical. This should be their obsession or their life’s work. Things take time. A lot can go wrong. And you have to be a strong storyteller. You often don’t have the kinds of commercial milestones that you’d see in traditional SaaS. You have to bring people along on the journey. On the go-to-market side, most companies are selling to just one, two, maybe three customers early on. You need to educate those customers. You need to understand their changing needs. Some problems are so critical that they won’t change. A million-qubit computer is still a million-qubit computer.
But with other bets, like in automation, we’ve learned that you don’t need anthropomorphic, five-fingered hands to solve the task. You don’t need a robot that folds clothes. You can create economic value by using robots in warehouses, as long as you know the requirements. So it’s about understanding where the tech meets the end customer. Talk to them early. There are only a few of them. That process helps define your product and sets the schedule for execution.
What industries or technologies are you most excited about for future growth?
We’re in a moment where localized industrialization is becoming more important. I don’t think we have to trade sustainability for economics. We can have both. Technology can be the lever that gets us there. I’m excited about any tech that creates a step change in existing systems. These are things that could lead to multi-billion dollar outcomes. When you look at global GDP, think about the physical sectors that are hard to change. If a breakthrough happens in one of those, it could reshape the entire economics of the space. That’s what I look for.
My favorite example – we backed a company called Ultima Genomics. Their mission was to revolutionize human genome sequencing. That technology isn’t new, but the economics around it have been limiting. Sequencing used to cost $1,000 per genome. If you needed a million patients, you were looking at $1 billion in data costs.
Ultima said, what if we could do it for $100, and eventually $10? Their approach pulled from the semiconductor industry using silicon photonics, automation and metrology. These are tools from the semiconductor world. They brought in expertise from outside the usual life sciences playbook and applied it in a new way. Now they offer genome sequencing for $80. That makes it possible to get a million-patient dataset for $80 million instead of $1 billion. That changes the cost structure for building personalized drugs.
That gave us an edge in building our thesis around platform therapeutics. We saw what was coming. And that’s the kind of thinking I want to see in other areas too. Can we do the same in agriculture? In construction? In manufacturing? Those are all fair game. They all need fresh ideas. I want to understand how we get to energy abundance and operational efficiency at scale. And once we have that abundance, what becomes possible? That’s a two-step process. First you solve for the constraint. Then you build on top of the leverage you’ve created. That gives you a long horizon for thinking and building. We love to hear from any founders who are thinking that way.
How do you define deep tech?
For me, deeptech isn’t just about working with hard technologies — it’s about building the future at a more fundamental level. At Playground Global, deeptech means tackling foundational problems where the bottleneck is real technology risk — not just market risk or execution risk. It’s about companies that, if successful, don’t just capture value — they physically change what’s possible in their industry. When a deeptech breakthrough works, it forces entire ecosystems to reorganize around it – like ubiquitous human genome sequencing or a million qubit quantum computer or EUV lithography that extends Moore’s Law.
Deeptech should move people to the next frontier.