Blond & Quantum: Early-Stage Startups — Featuring Ish Dhand | QC Design

In this episode of Blond & Quantum, I sit down with Ish Dhand, Founder and CEO of QC Design — a startup building the essential design automation (EDA) layer for fault-tolerant quantum computers.

We dive deep into why designing scalable, error-corrected quantum computers has become the industry's biggest bottleneck. Ish explains how QC Design is turning 30 years of academic research into production software, allowing hardware teams to simulate 20+ hardware imperfections at once — something open-source tools cannot do. We also explore why QC Design competes with in-house teams (not other startups), how they achieved product-market fit in just six months, and why they are already cash flow positive.

We also explore:

• What the "EDA layer" means for quantum (and why Cadence is the blueprint)
• The difference between logical qubits and logical sockets
• Why hiring 20 PhDs is hard to do — and how software replaces them
• How QC Design works across all hardware platforms (photonic, trapped ion, neutral atom, spin, superconducting)
• The 3–5 year roadmap to 100+ logical qubits solving transformative problems
• The real risk: what happens if no hardware platform reaches fault tolerance
• Ish's advice for anyone wanting to become a quantum founder today

🎙️ Guest: Ish Dhand | Founder & CEO, QC Design

🎧 Host: Eva | Blond & Quantum

If you enjoyed this conversation, don’t forget to like, subscribe, and share — more episodes with global leaders in quantum are coming soon.

Transcript

SPEAKER_01 0:00

Hey, my name is Eva, and this is Blond and Quantum, the podcast that breaks down quantum technology into real-world business impact. Here we make the complex simple. No equation, no overthinking, just insight, innovation, and a bit of humor. So don't worry, you don't need a PhD in physics to follow. In each episode, I talk to funders, scientists, and investors about how quantum is reshaping the industries today, not in some distant future. Oh, and if you heard a black cat boring in the background, that's my co-host, very alive shorting as a cat joining the conversation. Her name is Moon. Let's get started. Welcome everyone to the next episode of Blonde and Quantum. Today is a special one because we are just launching a brand new series dedicated to early stage startups in the quantum industry. And I couldn't be more excited to have as my first guest Ish Dant, founder and CEO of QC Design. Ish, thank you so much for being here with me today.

SPEAKER_00 1:11

It's my pleasure.

SPEAKER_01 1:12

Okay, so to kick uh things off, let me ask you in the beginning: what problem is QC Design solving?

SPEAKER_00 1:19

We are a quantum computing software startup. We are solving the problem of designing scalable quantum computers. So let's dig a bit more into that. Scalable here means quantum computers that are tolerant to errors, and hence you can just make them bigger and allow them to compute and solve bigger problems. And that's the field of fault tolerance. And designing fault-tolerant quantum computers is something which requires hundreds or thousands of physical qubits, chunks of matter or pulses of light that have to be very carefully put together, orchestrated, and this makes a logical qubit. A logical qubit is something which has noise profiles which are similar to the phone in your pocket. It has error rates which are very low, one part in less than a billion. And these almost noiseless logical qubits are what are needed basically for the transformative potential of quantum computing. So our product solves the problem of designing these logical qubits. And these logical qubits is basically where all the value of quantum computing is.

SPEAKER_01 2:26

That sounds very perfect. Okay. And um you worked previously at Xenadu, right? Um, you were working on the full-stack architecture. What made you realize? What was the moment when you realized that the middle layer should become its own compound?

SPEAKER_00 2:43

Yeah, it was a great time working at Xanadu. With the team, we built the first architecture for fault-tolerant quantum computing with photonics. The first truly scalable architecture for building a photonic quantum computer. And now the team has gone well, well beyond uh what we did back then and have started to realize parts of that computer. So that was the time at Zanadu. But also during this time, we realized that designing these scalable, fault-tolerant quantum computers is a very hard problem. It needs powerful simulations and it needs extremely rare expertise. So the expertise in fault-tolerant quantum computing, it's maybe 50 or so research groups worldwide that are producing PhDs. And there's more than 50 companies worldwide that are looking to hire these PhDs. So very, very hard to hire and retain this amazing talent. And what back then we did, and what so far I think most companies have been doing is they have these rare experts work on building and maintaining very powerful fast simulators to design fault tolerant quantum computers. This is really a waste of time and money. And we learned this actually after starting QC design that not only was Xana do facing this problem, but every single hardware company out there, ranging from companies working on neutral atoms like Pascal or Yakuma to trapped ions like INQ or Zuriq to photonics, of course, like Xana do, but also PsyQuantum. All of these companies have this challenge of building, of uh designing the best architectures for fault tolerance. And we learned this by basically just talking to all these hardware companies.

SPEAKER_01 4:20

And you can help excuse me, and then you can help all of those companies um do this error correction?

SPEAKER_00 4:27

Absolutely. So our software pluck it is used by companies across all hardware platforms, whether it's atoms, ions, spins. Recently we announced uh C12 as one of our customers based in France, working on spins to um to superconducting qubits and photonics as well.

SPEAKER_01 4:44

That's amazing. And I read on your website, I think, Eros, that when you describe yourself as an EDA layer, for our audience, EDA is an electronic design automatic. So basically it's a software where it's used to design hardware, however it sounds, right? Um so you you describe yourself as an ADA layer for quantum computing, similar to the cadence design system, the legendary component from Sandhosa, which every single computer uh designer using um in the world. So, what has to be true for this layer in the quantum world to become indispensable? And basically QC become that's the hope, right?

SPEAKER_00 5:33

So EDA is indispensable to where we are today in semicon. Whether it's again the phone that we are using that has a billion transistors or GPOs running the latest AI models that have far more transistors on these chips, being able to put them together and make them work reliably is of course impossible for a human. It already became impossible for a human 30, 35 years ago. And at that time, companies like Cadence and Synopsis and previously Mentographics, as well as some open source efforts out of Berkeley and Stanford, uh going all the way back to 1970, all of these efforts have taken us from a time when it was actually humans drawing chip layouts literally on some material to a system where we could start specifying components that'll put together that'll make a semicon chip and simulate it. And then to, for example, the compilers from Synopsis that will allow human readable logic to be translated into design of physical chips. All of these advancements over the years have led us to where we are in semicon. So the EDA industry is very quiet, uses products, no end user uses their products so much, but every semicon company is using EDA tools to design chips, and basically 3 to 5% of the entire semicon industry is EDA. So EDA is really very, very important in semicon. As quantum computing also goes from a time when right now we have a handful of qubits to a time when we'll start to put hundreds and thousands of qubits together into these logical qubits that I mentioned, then this is the time when we really need a design layer. We need to be able to understand all the imperfections that arise in quantum systems. And we need to be able to understand how to put quantum systems together to make these noiseless logical qubits. And basically that's the problem that uh we're solving. So maybe to answer your question of okay, when does quantum design automation become indispensable for quantum? I would say it's right now the industry going from putting together a few qubits into noisy NISC devices that can solve a couple of problems, to the industry really now shifting its focus on building large-scale fault-tolerant quantum computers.

SPEAKER_01 7:57

Yeah. Okay. And this is exactly what your first product, which is Plughead, is doing, right? Can you take us a little bit more through the journey? What actually happened when the hardware company actually uses it? Using as much as possible, plain English, please.

SPEAKER_00 8:12

All right, let's give it a shot. Let's give it a shot. Our customers are quantum hardware manufacturers. These are companies that are trying to design and build large-scale useful quantum computers. When they start working with us, these could be for two different problems that they solve and they're very closely connected. One is to demonstrate near-term logical qubits or logical circuits. So, for instance, the legendary examples from the last couple of years have been, for example, from Google or Quantinium or other companies where they show, okay, we can take a few physical qubits, let's say 17 physical qubits, and then start increasing the number of physical qubits that you put into a single logical qubit and get a less noisy logical qubit. So this is this idea of below threshold performance. So these first demonstrations of logical qubit, you of course need to understand what are the 20 different sources of noise acting on the system and which ones you need to work on to improve. Yeah. So uh there are, in the end, when we want to build a useful quantum computer, you want to take a classical problem. For example, simulate this molecule or tell me this energy level of this molecule. That's a classical problem. We use a quantum algorithm to solve that problem, which basically says, okay, there's a quantum computer sitting in between the classical input and the classical outputs. This quantum computer takes those classical inputs into qubits which are talking to each other through some kind of gates or similar operations. And how these qubits are interacting with each other, and hopefully how these ideal noiseless qubits are interacting with each other, that's the logical circuit. And of course, the logical circuit is comprised of logical qubits, individual maybe patches or some funny contraptions similar to patches of a whole bunch of physical qubits that together uh form this noiseless logical qubit.

SPEAKER_01 10:07

Okay, so basically it's a group of logical qubits working together and on the same problem. Okay, perfect. Now can you please tell us a little bit? Uh so from my understanding, you're turning um or you're trying to turn the quantum error correction from a research problem into engineering discipline to help those companies to scale. Um what's the hardest technical barrier that you are still working on or is still standing there and need to be um solved?

SPEAKER_00 10:39

Yeah, uh the first part of the question or the first comment, this is really the thing that makes Plucket useful, is that we take 30 years of academic research and publications and turn it into production quality software, something that our customers can just use with two lines of code. And for us, the biggest challenge in the past, let's say, let's say six to twelve months ago, was to understand what makes it truly useful. And in the last, again, six months or so, we've been fortunate to be able to work with companies from across all hardware platforms. So we really understand what is it that matters for all of these hardware platforms, what are the main fault tolerance design problems? And basically, then we listen to our customers very carefully. We build what is important for our customers and all the customers that'll come for us in the future. For us, this has been the main focus, this has been the central challenge. And I would say it's a challenge which is more or less overcome now by the team.

SPEAKER_01 11:38

By the team. That's congratulations. That's amazing news. Speaking of your customers, actually, I want to um dig a little bit deeper into it. So you mentioned you work with most of the hardware companies. Who is your first true ideal customer and what is the success deployment looks like for you and for for them?

SPEAKER_00 11:57

Yeah, uh, we have customers really across the full spectrum. So I mentioned all hardware platforms, but also we have customers who started out six months ago building a quantum computer or customers who started 10 years ago building a quantum computer. So it's really basically the full span of the industry in terms of maturity. And I think to answer the ideal customer question, there's customers who are just starting out on their fault tolerance journey. Maybe they've been able to hire one of these rare fault tolerance experts, and we bring in our tool and our expertise and allow this one person team to function as basically 10 to 20 people team and move much, much faster than any competitors who are not using Pluckhead. So, with that, they can design the best architectures. With that, these small teams can basically come up with the best logical qubit and logical circuit demonstrations. But also maybe thinking about the more mature companies. These are companies who have already clear ideas of how they want to have the first quantum computers be built, but want to improve. So it's not zero to one, but it's mostly 10 to 100 in terms of performance of the architectures. And these companies already come to us with kind of their own internal representations of how they will do fault tolerance. This is becoming more and more standard these days, what kind of representations people use. And our tool takes those precise representations, they start working with the same internal representations and tells them much more than what their own in-house tools could tell them or what open source software could tell them. So if somebody is using an open source software to understand which hardware imperfection is important for their fault-tolerant quantum computer, they know that two imperfections are accounted for. With our software, we can account for any imperfection, which includes 20 or more imperfections that actually matter to the hardware customers. So suddenly they go from being able to see the impact of two imperfections to being able to see the impact of 20 or more. And this is uh really very, very valuable information that helps them move along faster. Those are the two use cases uh for early teams and for later stage or more advanced teams.

SPEAKER_01 14:08

So in terms of okay, so in terms of the deployment, you provide the software and you provide your team helping them to solve those problems, or you train the in in in-house team for them.

SPEAKER_00 14:23

Yeah, for us, we are lucky that we can learn from EDA tools, from EDA suppliers about how they do, how they work with customers. So most of the contract, most of the value comes already from our customers having access to the software. We actually provide on-premise software, which allows customers to run their own simulations, validate their own designs without telling us anything. So their IP stays on their computers, which is something which they value very much. Then a small part of the contract, which is optional often, is service hours. And in these service hours, if there is something which has to be developed for a particular customer, but it has to be something which really matters very much to them and matters very much to the industry, then we are happy to build this. But overall, every customer that we work with, we basically pride ourselves on having the best customer support in the world. Customers come to us with hey, wouldn't it be awesome to have this error correction code from this particular paper be in the software? And within a matter of days, we're able to put it in the software. In February, for instance, we had 10 upgrades to Pluck It, so two and a half upgrades per week. And 100% of these upgrades were based on requests or feedback from customers. So the product gets very useful very fast for all the customers thanks to the feedback we're getting from all of them.

SPEAKER_01 15:45

My goodness, that's definitely um very dynamic speed pace that you implemented. And congratulations for that. May I ask, how many people do you have in your team?

SPEAKER_00 15:54

Yeah, we have about 15 people and all of us, and I think it's really these 15 people who should be congratulated for the incredible release velocity and incredible basically product flywheel that we have.

SPEAKER_01 16:06

100%. And I wanted to ask you also about the business model working with your clients right now. So when you approach the client and when you start working with them, are you offering any POC SFLs, any trial period, or you charge them from the day zero?

SPEAKER_00 16:20

So there was a time early last year when we were working in terms of POCs. That's because the product was not yet there. In the last 12 months, everything has changed in the sense that we know what it is that makes the product useful. We've built that. And we are also able to communicate this value clearly enough to the customers. So basically, we offer annual subscriptions, and these annual subscriptions allow customers uh to basically have um an equivalent of a team of 10 to 20 people. So if they would not use Plucket, the alternative for them would be to hire 10 to 20 people in-house, which is extremely rare and actually impossible in many cases uh to hire these experts. And the value of that team we are able to provide through our software. So they're able to move much faster than any of their competitors.

SPEAKER_01 17:12

You you said they're not able to hire 10 to 20 experts because simply there's not enough of them on the market. Yes. That's what you mean. Okay, great. Um, and may I ask, are you charging them a fixed fee or is it per seat in a sense?

SPEAKER_00 17:27

Yeah, so it really we want to make sure that we are able to cater to the smallest startups that we work with, with one or two people teams, but also we want to make sure that we are able to grow alongside our customers. So again, we follow standard practices from EDA. There is a certain price for the first couple of seats, and then it increases linearly with the number of seats.

SPEAKER_01 17:52

I want to switch a little bit of topic right now and talk a little bit about your competitors. So with the players on the market like Entropical Labs and River Lane in the UK and um the others, they are tackling, from my understanding, a different part of error problem. You mentioned that you are able to solve all of them, a lot of them, on different angles. So I want to ask you where do you believe QC Design will uniquely win and where potentially do you expect others to dominate?

SPEAKER_00 18:23

Yeah, these are all great companies, Entropica, Rivalin, Q Control, and so on. There's many companies right now working on correcting errors, working on improving performance of quantum computers. My understanding is that all these companies are working on different problems of the users, which is I think a great position for the industry because we need to focus on advancing the industry together. So Q-Control works on suppressing errors, and this is a different layer. It makes physical qubits and physical gates less noisy. And we work on the next layer of the stack, which is logical qubits and logical gates. So actually, these two stacks come together very well because the performance improvements that you get from both of these can improve. We actually announced a partnership with Q-Control quite recently to actually demonstrate this compounding effect of these two parts of the stack. Entropica, from what I understand, builds tools that help orchestrate logical qubits. Once the qubit is designed, then what do you do after that? And Riverlane is making these incredible decoding chips that have to be very, very fast and have to have super low latency to find and correct the errors on the actual logical qubits. We know several customers who are using tools from all of these companies. And of course, in the future, there will be many, many similar parts of the stack that other companies will address. So, okay, maybe then coming back to the original question of competition. For us, the competitive alternate for our customers, if they want to not use Pluckett, then what do they do? It is that they need to build these tools in-house and maintain them for several years. This is always the competition for us, as it has been the competition for all the EDA giants, like Kiddens and Synopsis. Our belief, our very strong belief, especially after working with customers, is that as a standalone company, we have the possibility to focus on this problem, to learn about error correction and make the best error correction tool for all platforms and have our own flywheel running. And this allows basically us to specialize and us to be able to help everyone and basically do this for much less cost, but also much, much faster than having to build an in-house team for this software.

SPEAKER_01 20:35

So this is very interesting, ish ish what you said, because that is mean that the other companies are not basically your competitors, they are a complementary company. And uh congratulations on the partnerships with um Q Control. So that's I wasn't aware about that, that you basically compete with in-house teams much more than uh other startups in the field. So if I may and that brings me to the question why was now the right time to build a company in this part of the quantum stack?

SPEAKER_00 21:08

It's really the time for fault-tolerant quantum computing. These last one to two years have seen an explosion of hardware teams demonstrating incredible logical qubits. Every hardware team across many different platforms has efforts to demonstrate putting together physical qubits into noiseless or less noisy logical qubits, as well as efforts on long-term roadmaps. So many of the serious quantum computing teams know that in the next three to five years they're going to build useful fault tolerant quantum computers. So everyone is starting to ramp up their design efforts. And this means that for them, basically, they need design tools like what we provide. So I feel like this is also a big part of why we found product market fit about six months ago, where the product got to a stage where it was suddenly. Very useful for many companies, but also many companies came to a stage where they could actually start to find value in buying the software from a provider like us. And I think this is uh great for, of course, QC design, but also a great time for the industry.

SPEAKER_01 22:14

So let's talk a little bit about the future, actually. You find, as you said, your product markets fit in six months. That's amazing. What are the next milestones that will define your company? Who's the next phase for your company?

SPEAKER_00 22:28

I think for us, the the big change that happened was again six months ago when we found product market fit. The most important thing for us to do now is to do more of what we've been doing recently. So this means keep listening to our customers, keep trying to understand what makes Pluckett more useful. And basically, based on this listening, keep building Pluckett into this most useful tool for them. We expect that quantum computing will grow very fast. Tolerance will come very fast. Hopefully, QC design can contribute to it coming faster. And as the industry grows, then we will be leading in this design automation industry within quantum computing. So just like uh uh EDA companies grew alongside the semicon market in this three to five percent number, and semicon itself exploding exponentially, we expect that it'll be very similar in quantum, just with hopefully more compressed timelines and uh and being able to generate uh true value for humanity very soon.

SPEAKER_01 23:25

This is amazing. But let's talk a little bit about the risk. We do have some, I know we do have some investors in our audience, and they may think, okay, this all sounds like uh fair tape. Quick market fit, a lot of customers, um, you know, first revenue in less than 12 months of existence, a very proven path from EDEA. What could go wrong ish for QC design potentially, or for this entire approach to the error correction? Is there any any fundamental risk that something can shift so much on the market that you know you will need to pivot or change your approach or the whole concept may not succeed?

SPEAKER_00 24:09

We think about this all the time, of course. Uh, we want to make sure that uh we are able to succeed and the industry is able to succeed. So from the beginning of us building Pluckett, we've kept it platform agnostic. So if any of the five or six hardware platforms gets to fault tolerance, we are able to win alongside that platform. My belief is that there will be actually multiple winners or combinations or hybrid winners basically. And we think that if this is the case, of course, we'll be able to win alongside that. And there are companies across all hardware platforms that have a plan to get to 50 or 100 logical qubits in the next three to five years. So the risk, of course, is hardware. Building hardware is very hard and timelines could slip. It could happen hypothetically that no hardware platform is able to get to fault tolerant quantum computers. I do not believe this will be the case. There's many, many smart people working very hard on building fault-tolerant quantum computers in our customers' organizations. So for us, the risk is that no hardware platform gets to fault tolerance. If even a single hardware platform gets to fault tolerance, there'll be many more companies who will be building on that platform. And uh and then QC design is of course relevant and hopefully winning and leading in the design automation side of quantum computing.

SPEAKER_01 25:22

This is very interesting. So basically, what you're saying is that in in the worst case scenario, if only one hardware approach will win, because you are platform agnostic, you can basically follow this specific approach and still be successful and still be a built billion, two, three billion um valuation company.

SPEAKER_00 25:42

Yes.

SPEAKER_01 25:43

Fantastic. And I wish you that. Thank you. Uh and let's talk a little bit about the funding. How did you fund the company? How much did you raise from the market? Who are your investors and what are the plans for the future runs?

SPEAKER_00 25:58

Yeah, we got started about four years ago, and uh we raised a small uh low million digit euro amount about four years ago. From uh actually, we've been super fortunate with the investors that we've been working with. Uh Quantination, of course, I understand you're also associated with Quantation after we were associated with Quantination. So being able to work with Quantination has been awesome because we get a network of every quantum computing company or across all different platforms straight from our investors. Uh, but also we work, uh one of our other investors is Square Ventures based in Munich, uh, who were one of the early backers of IQM and uh also of many other deep tech companies. Plus, we have a third investor who earlier was the chairman of BioNTech, the company that made the vaccines. So we've been fortunate to have investors who understand the challenges of quantum computing, understand the time scales, understand the talent shortage. All of this is something which we can have really honest conversations and conversations with the investors about. So that's been uh uh investment round that we raised four years ago. And since then, we've also gotten public funding, about 1 million euros from the German uh BMBF, the now called BMFTR, and about 2.5 million uh from the European Innovation Council. And these two uh grants have been non-dilutive, so 3.5 million euros in non-dilutive funding. And uh that's been the past. Right now, uh, thanks to the grants and thanks to our revenues, we are actually in a cash flow positive situation.

SPEAKER_01 27:30

Well done.

SPEAKER_00 27:31

Which thank you. Which I think uh, of course, the team has really worked very hard on getting us to this situation. So this allows us the flexibility to grow as fast as we want. And uh that's we are what we are doing right now. So listening to our customers, building the product, making it more useful, and growing the team alongside this at this pace. Of course, we will want to raise another round in the future, in the not too distant future, because we think that the market for quantum design automation is very large, and we want to be able to really provide value to this market, which means more growth, and uh this is something that we might do very soon as well.

SPEAKER_01 28:10

Um, you know, having this discomfort of bootstrapping for a while, I think is a dream for many startups, not only in the quantum industries. Before we wrap up, because we're coming to the 45-minute threshold, I would like to ask you as well a little bit about quantum advantage. So, what does the quantum advantage actually mean in your world, in the business terms, not in the theory?

SPEAKER_00 28:37

I think the thing that really matters in terms of advantage here is we should be able to have quantum computers that are large enough that they can solve transformative problems, problems that have billion dollar or more value generated for the economy and for the society. And we know that there are quite some problems of this sort. So designing new materials like batteries or designing new molecules like pharmaceuticals or vaccines and so on, these are problems which require simulating chemistry, which requires quantum mechanics, or quantum computers are very, very good at this. And this is the first set of problems that will be transformative. There will be many other problems that will come later, but already with somewhere between 100 and 1,000 noiseless logical qubits, which is off the order of five years away, we expect that quantum computers will be able to tackle these transformative problems.

SPEAKER_01 29:32

That sounds pretty good. Thank you so much. And as a last question, one piece of advice for someone who is right now building in the quantum industry today, or someone who's thinking to start the building and becoming a founder.

SPEAKER_00 29:48

Maybe first for the latter, if you're starting uh to think about becoming a founder, just do it, just go for it. You'll uh of course learn a lot and uh the impact that you'll be able to have is really unmatched. So that's just an aside for anyone wanting to be a founder in quantum computing. But in terms of what problems to work on, I think we as an industry really need to keep working. I think a lot of companies right now are working on this, keep working on getting to that transformative value. On this three to five year horizon, when we have hundred plus logical, noiseless logical qubits, that can solve problems that truly matter to society and economy. And I think there's lots of problems within this high-level problem right now. For us, it's the design of all quantum computers. And for many other companies, it could be different parts of this problem. But we as an industry just gotta keep chipping away at this massive problem and uh and take us to transformative quantum computing.

SPEAKER_01 30:44

So, ladies and gentlemen, that was Ish Dank, a founder and CEO of QC Design. Hopefully, the next cadence systems uh in the future in the quantum world. So it was my pleasure, Ish, and looking forward to seeing you in person one day, and maybe on the next um quantum nation event.

SPEAKER_00 31:04

Absolutely. Thanks so much for having me here.

SPEAKER_01 31:06

Thank you so much. That was Blonde and Quantum. Thank you for joining me on this journey through the quantum business frontier. If you like the episode, please review another Spotify or Apple Podcast and help more people discover the quantum world without needing to untangle the theoretical physics. See you next time. Unless the cat change the timeline first.