What Crypto Already Solved for Enterprise AI | Rami Akeela | Nera Systems

Not everything is a Kodak moment, but for that Kodak moment to happen, a lot of work needs to be put into it. You start to feel joy doing the mundane stuff and the boring stuff and the hectic stuff. And I think that's what I'm experiencing building these startups. I feel like it, it has a purpose.

When, how tired you keep going, even if you're running with fumes, it doesn't matter. that you believe in this thing. You want to see it in the hands of more people. You want to see it add more value, fix real problems.

So you keep going. And it doesn't matter how tough it gets. This all means nothing when you see the fruit of your work. This is Money Never Sleeps.

Sharp riffs, big ideas, and real insights from smart people. I'm Pete Townsend, GP at Norio Ventures. Let's go. Money never sleeps, pal.

Rami Akhila has spent 20 years building privacy and cryptographic infrastructure that most people didn't know they needed yet. Now, he's the founder of Nira Systems, solving the conundrum that's about to define enterprise AI. The more valuable the data, the less you can use it. And a quick disclosure, I invested in Nira via Techstars in 2025, so I've got a front row seat on this one.

Rami, welcome to the show. Thank you for having me. Appreciate it. You've been building zero-knowledge proof systems for years.

What did that teach you that most AI founders simply don't know yet, Rami? In zero-knowledge proofs, the idea was I could still prove that something is right and not have to expose my most sensitive data. And, of course, on top of that, so many things were built. Some of the coolest applications were built.

And the same premise can actually be applicable in an AI again, which is I can do so and so with AI without actually exposing my data. Of course, everybody has sensitive data with its patient records, transactional records. But the idea is how can I actually build the system on top of this? It's not a question of can I actually use it securely and privately?

No, we know we can. Again, it's a matter of how do we actually build systems that would allow for AI intelligence to be extracted while protecting our data. Instead of actually saying, yo, everybody is basically saying, if this is too sensitive, then I shouldn't be using it with AI. So the answer is basically either or.

And that's what we're trying to crack. It doesn't have to be a paradox. Almost like saying science has proven that we are able to get a starship from Earth to Mars. What do we actually do when we get there?

Right Exactly Exactly Yeah Okay Because it is a problem of people not realizing that such institutions exist And so what is happening now is the fact that we have locked data This is too sensitive then, and we can't use with AI because then it will be exposed. Now that they know that this can be done, all this gets unlocked. So this is data we can process. This is insights that we can get from our most sensitive data.

And now that they know that this can be done, the opportunity becomes a lot bigger. Give me a couple of examples. When you and I first met Remy, the things that immediately jumped out at me were the sensitivity of financial data in terms of retail, customer, financial services data, banks, fintechs, whatever, and also healthcare data. So your most sensitive patient data that you have when hospitals are tracking everything about you when you go to see them to be treated for a certain thing.

And that is incredibly sensitive data. Now, most people don't think about the fact that, hey, could this healthcare worker just take all of my medical files and pop them into Claude and say, hey, can you look at everything else here and see what's really going on with this person? or that a large bank would take millions and millions of lines of data and feed it into chat GPT with all of their most sensitive client data and say, can you give me some analytics here on the demographics of all the people who might be eligible for spending more and creating more of a revenue opportunity for us on interchange on credit cards or give us an opportunity to cross sell.

So banks, financial services providers, healthcare, wouldn't just drop this data into ChatGPT and or Claude today because they know that once that data is with inside the walls of open AI, in ChatGPT's case, or Anthropic, in Claude's case, that it's open season. And so you're not going to do that. Are these kind of the two biggest use cases that you're pointing to for being able to run AI on data sets securely and privately? So, yes, if you're in a bank or some client shafir, then you're absolutely right.

We shouldn't be uploading these records to ChatGVT and Claude to get insights. The reports are basically saying it's close to 70, 80% of employees use ChatGVT secretly. So we know this is happening. Employers know this is happening.

In hospitals, I know I have friends in the medical field and they tell me they, nurses, doctors, are always uploading stuff to TGPT to get answers in seconds. Because they're under a lot of pressure, but they do that violating HIPAA, obviously. We know this is happening but those are the most obvious ones But then you have cases where we talk to accounting firms and basically an account needs to run say taxes on their data They know they can just use AI and say about a lot of time and actually take on more, again, some people are just doing it, violating all kinds of client data, confidentiality rules around that.

So this is a solution for them. This is a solution for private equity firms where they need to run diligence. We worked with CPG firms on their retailer data so they can then sell to manufacturers. You can see it playing out in every vertical because again, if that solution exists, then I got to think of ways I can utilize this solution without having to make or accept any compromises.

When you talk about sensitive data, you're no longer talking about medics and hospitals and defense. You're talking a lot about every single business and how they should protect it. There are big companies who have their own internal AI models, their own LLMs that they're running, and that where all of the data stays within their own closed walled garden. But only the biggest and best companies with the largest tech budgets can really afford to do that.

Looking at the personal journey that you've gone through, Rami, with your earlier startups in mind, was there a certain point where you realized that you've been training for this problem the whole time? You got to trust the process. Just go through this journey, learn, make mistakes, but keep going. Every time you fall, get back on your feet and keep going.

That's the main lesson. I'm happy that I stayed on my path because I didn't realize that I was building to this point. How I got to understand privacy enhancing technologies, how I got to build systems for different applications and domains. And I was doing that while I was doing a PhD.

How do I take a really complex problem and put it in simple terms so people can understand? How do you actually go from research papers to actual products that you can ship? It all led to one point. It was like, you need to build this before it even becomes a tangible problem.

Because you can see it. Because you've been trained to see problems in the early days. And so, yeah, every day I'm reminded that something happened in the past had a purpose, had a reason. And it's all to get me to this point.

Through this whole process of the prior startups, your time in academia, everything, that, you know, getting to this point now with Neera, what's kept you building through the parts that had nothing to do with cryptography? All the other things that you need to do as a founder with fundraising with pitches with the grind underneath all of that What kept you going The fact that I doing something of value outside of my comfort zone But you know the more I do it the more I enjoy it Connecting with people pitching handling the boring stuff like HR and payroll and accounting and filing taxes.

Doing the necessary part of what would allow for me and Neera to make this happen. On a personal note, for example, I'm a husband, I'm a father. That's what you got to do. And I love it.

I'm sure it's a lot of work, right? Not everything is a Kodak moment. No. But for that Kodak moment to happen, a lot of work needs to be put into it.

You start to feel joy doing the mundane stuff and the boring stuff and the hectic stuff. And I think that's what I'm experiencing building these startups. I feel like it, it has a purpose. no matter how tired you keep going even if you're running with fumes it doesn't matter because you believe in this thing you want to see it in the hands of more people you want to see it add more value fix real problems so you keep going and it doesn't matter how tough it gets and you you know some of the stuff that i went through i'm still going through this all means nothing when you see the fruit of your work yeah i know what you mean and it's like i'm staring at this book right now in front of me, which I've read only a bit of.

It's David White Essentials. He's an Irish poet. And that word essentials, what are the essential things you must be doing? I keep that on my desk so that I focus on that because it's sometimes that extra 5% that you've got to put into your day that makes 50% of tomorrow happen a lot better.

And so it's just whatever works to keep moving is what you need, right? Yeah, yeah, 100%. Very good, very good. Well, Remy, listen, that's a great place to end it.

Where can people find out more about you and Nero Systems? Nero.systems, N-E-R-A.systems.

The website should have plenty of information about what we're doing. It also has, under Solutions, you'll find our chat app, where people can try it for two or three weeks and see the value it can add to your data. But me personally, I'm happy to connect with people over LinkedIn. That's under my name, Rami Akila, R-A-M-I-A-K-E-L-A.

And feel free to reach out to talk about anything beta and AI related or really anything else. I'm always happy to talk with Morris though. I could attest to that. I could attest to that.

Wonderful. Well, listen, thank you, Rami. I really appreciate you joining the show. And to all of you out there, thanks for watching and listening.

Don't forget to follow or subscribe wherever you get your podcasts. helps others to find the show and it means a heck of a lot to me. Till next time, see ya!