Former Docker VP Reveals the AI Security Gap Costing Teams 80 Hours

Summary

Podcast Summary: Lead With AI

Episode: Former Docker VP Reveals the AI Security Gap Costing Teams 80 Hours
Host: Dr. Tamara Nall
Guest: Jesse Williams, Co-Founder and COO, Jozu
Air Date: December 9, 2025

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Episode Overview

This episode of Lead With AI features Jesse Williams, former Docker VP and now the COO and Co-Founder of Jozu, an AI DevOps platform. Dr. Tamara Nall digs into how Jozu addresses critical gaps in AI security and governance that leave many enterprises vulnerable—and wasteful. They discuss the importance of robust standards in machine learning (ML) deployment, real-life business impacts, and the future of operationalizing AI, focusing on practical solutions over hype.

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Key Discussion Points & Insights

1. Jesse’s Background and Motivation

• Tech Experience: 15 years in tech, roles at Red Hat, IBM, AWS, VP at Docker.
• Personal Drive: “At my core, I’m a dad. I love being a dad. … My motivation is all about my kids, just providing for them.” (Jesse Williams, 02:06)
• Finds excitement and ongoing engagement in leading-edge tech.

2. What is Jozu?

• Core Focus: Helps enterprises get ML models into production quickly and securely, aligning with existing software standards.
• Problem Addressed: Traditional software governance frameworks didn't keep pace with the rapid adoption of AI/ML, creating risky security gaps.
• Innovation: Developed KitOps, an open-source project for artifact-based AI governance, now used by Red Hat, PayPal, ByteDance, and more.
  • “All the things that we’ve done to make sure our applications are trustworthy are non existent, even down to some of the most basic things like application versioning.” (Jesse Williams, 04:11)
  • KitOps is now under CNCF and has inspired the Model Pack spec.

3. The "Holy Smokes" Moment for Users

• Key Realization: Most teams think they have versioning handled, but Jozu reveals a single, tamper-proof artifact is missing.
  • “When we show them that open source project, Kit Ops, and we say, hey, this is all going to go into one artifact that is tamper proof… That’s where the light bulbs start going off and people start thinking, wow, I can do ML just as easily as I can do a microservices application.” (Jesse Williams, 06:16)

4. Under the Hood: How Does Jozu Work?

• Central Registry: Functions like ECR or Docker Hub but tailored for ML.
• Unique Add-ons: Handles diffs for prompts (critical given their length and complexity), package inference, effortless model deployment via Docker, and Kubernetes compatibility.
• Security Layers:
  • Integrated open-source security tools into a unified interface.
  • Cryptographically signed, tamper-proof audit logs—huge time savings.
    • “We’ve heard teams that take two developers two to three weeks to create a full audit log of their model and Jozu services that automatically.” (Jesse Williams, 09:54)

5. Practical, Even for Non-Developers

• Ease of Use: Allows non-technical users to pull models from Hugging Face and package them with minimal commands.
  • “For me, as someone who’s not super technical, I wouldn’t have been able to probably do that without significant help from ChatGPT.” (Jesse Williams, 11:44)
• Tool-Agnostic: Works with many model types, not just LLMs.

6. Naming Story

• Jozu: Japanese for “skilled or tactful,” inspired by co-founder Brad’s time in Japan. (13:04)

7. Ethics & Governance in AI

• Focus is on robust process controls, not just outputs.
• Key example: Preventing sensitive data (e.g., credit cards, medical info) from being included in models; compliance with HIPAA, GDPR.
• “We put governance into place so that … the things composing this model [are] the right things or not.” (Jesse Williams, 14:42)
• Considers cross-company and international data boundaries, model licensing, and embargoed regions.

8. The Future of AI Operations (MLOps)

• Emerging Trend: Shift toward on-premises and open-source AI models.
• Vision: Internal teams operationalizing critical AI workloads with Jozu, not just surface use-cases like chatbots.
  • “Our ideal future … is actually teams starting to operationalize ML inside of their business… not just having a support chat bot but internal, really important, really secure data.” (Jesse Williams, 17:28)
• On-Prem vs. Cloud: On-prem remains crucial for high-security, internal business. The main drawback is more in-house maintenance.

9. Getting Started and Community

• Try KitOps: Open-source, vibrant Discord community.
• Jozu Demo: Free sandbox at [jozu.com], with full feature POCs available.

10. Personal Insights & Bonus Segment

From One Genius to Another (19:56)

• Cherished Memory: Learning to ride a bike alone as a child. “I felt like I was flying.” (Jesse Williams, 20:09)

Rapid Fire Round

• Most Overrated AI Trend: “996 culture” (working 9am-9pm, 6 days/week) – “You get most of your creativity outside of the workplace.” (Jesse Williams, 21:22)
• Most Underhyped AI Trend: Custom GPTs—deeply training a GPT for a specific skill or task.
• Book Recommendation: Hackers & Painters by Paul Graham. “It’s also just a beautiful book, the way that it’s written.” (Jesse Williams, 22:43)
• Boldest AI Prediction: AI will enable more personal entrepreneurship. Predicts rise of billion-dollar 10-person companies.
  • “AI is going to open up the opportunity for everyone to basically be their own entrepreneur if they want to.” (Jesse Williams, 23:20)

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Notable Quotes & Moments

• On security gaps in AI deployment:
  “ML came around so quickly that a lot of those things that we depended on to make sure our company doesn’t end up in the news for doing something bad … kind of got skipped and all of a sudden AI was here.” (Jesse Williams, 03:46)

• On why open source matters:
  “We built [KitOps] on open source … now it’s been adopted by companies like Red Hat, by PayPal, by ByteDance, the TikTok creators.” (Jesse Williams, 04:41)

• On personal creativity:
  “You get most of your creativity outside of the workplace, so work hard nine to five, put 40 hours in and you’ll be good.” (Jesse Williams, 21:30)

• On AI’s impact on opportunity:
  “I think it’s actually going to open up more opportunities for people.” (Jesse Williams, 23:37)

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Important Timestamps

• 02:06 — Jesse discusses career, family, and motivation
• 03:05 — What Jozu does and why it was started
• 04:11 — The missing standards in ML security and governance
• 06:16 — Describing the “aha!” moment for users
• 09:54 — How Jozu automates audit logs, saving weeks of developer time
• 11:44 — Ease of packaging models without deep ML expertise
• 13:04 — The origin of the name Jozu
• 14:42 — Jozu’s approach to ethics and data governance in AI
• 17:28 — Vision for on-prem and future AI workloads
• 19:56 — Cherished childhood memory: learning to ride a bike
• 21:07-23:39 — Rapid fire (overrated/underrated trends, book rec, bold prediction)

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How to Experience Jozu

• KitOps Project: kitops.org – free, open source
• Jozu Platform & Sandbox: jozu.com – demo access
• Connect with Jesse: LinkedIn (Jesse Williams), email ([e-mail])
• Community: Vibrant Discord for devs and users

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Tone and Takeaway

Warm, down-to-earth, and practical—this episode avoids hype, focusing on authentic stories and significant, real-world challenges in AI governance and deployment. By the end, even non-technical listeners understand the urgency and impact of AI security gaps, the practical solutions Jozu provides, and feel inspired by Jesse’s vision of an AI-powered, opportunity-rich future.

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For more conversation, insights, and firsthand innovation stories, subscribe to Lead With AI and join the discussion shaping the future of artificial intelligence.

Transcript

[Dr. Tamara Nall]

Welcome to Lead with AI, where we.

Explore the minds building the future of artificial intelligence. Today, we're talking with the team behind Jozu, an enterprise DevOps platform that treats AI governance like mission control for the entire digital universe. If you've ever wondered how companies can innovate boldly and stay secure, this conversation with Jesse is for you. Let's get into it.

Welcome to lead with AI. I'm Dr. Tamara Nall. In each episode, we will take you behind the scenes with visionary leaders shaping the future of AI across public and private sectors. Join us as we explore groundbreaking projects and innovations that are transforming industries and making a real impact on people's lives. Let's dive in.

Hi, everyone. How are you? It is your hostess for lead with AI. I'm Dr. Tamara Nall and I am so thrilled to have Jesse Williams here who is the co founder and COO of Joe Zoo. How are you, Jesse?

[Jesse Williams]

I'm good, Tamara. Thank you so much for having me on.

[Dr. Tamara Nall]

Absolutely. And I always like to thank our guests for being here. We were number one in technology on Apple Podcasts in June of 2025. We had a good month and a have run there and then we recently found out that we're the winner of W3, which is a huge deal for podcasts. But it wouldn't be possible without great founders like you, Jesse, and of course great AI products like Joe Zoo. So we're going to get into it because I'm excited about what Joe Zoo does for developers and creators.

[Jesse Williams]

All right. And congratulations.

[Dr. Tamara Nall]

Thank you, thank you, thank you, thank you. So let's start with who you are, Jesse. We always like to know who are you at your core, what's your passion and how that syncs and links up to your starting Josu.

[Jesse Williams]

Yeah, well, so I'm a 15 year tech veteran. That's kind of my career background. Been in and out of the startup space. Spent a lot of time climbing the corporate ladder, honestly through acquisitions. So did red hat, IBM, AWS, was a VP at Docker. @ my core, though, I have to be honest, I'm. I'm a dad. I love being a dad. I've got three kids in the family. My, my, my pride and joy there. And it's really, you know, I think a lot of people have different motivations for their career. Mine is, yeah, it's, it's all about my kids, just providing for them and that's what I love, getting to innovate and I'll get to tell you a little bit about that. But yeah, being on the, on the, you know, leading edge of technology is something that excites me and it keeps me engaged throughout the.

[Dr. Tamara Nall]

Days. That's amazing. So, yeah, tell us a little bit about Josu. Tell us, what is it? What does it.

[Jesse Williams]

Do? Yeah. So Josu helps companies get their ML into production quickly and securely and in a way that really works with existing standards, is like what we like to call.

[Dr. Tamara Nall]

Them.

[Jesse Williams]

Okay. And I guess to maybe take a double click in there for people that aren't technical. We've been building software for a long time. You know, 15, 20 years we've been deploying software and through that time we've come up with processes and governance and ways to do it securely, ways to do it quickly that have become proven and trusted. ML came around so quickly that a lot of those things that we depended on to make sure that our company doesn't end up in the news for doing something bad like leaking everyone's data. It kind of got skipped and all of a sudden AI was here.

What my team did is we have extensive background in DevOps and developer tooling and we looked at the, at how AI was being developed and we said, well, this is really, really risky. All the things that we've done to make sure our applications are trustworthy are non existent, even down to some of the most basic things like application versioning. And so we started building that and Josu is really the baseline for that and we built it on open source. And so technology that we pioneered called Kit Ops, we've actually donated to the Cloud Native Computing foundation so that everyone can use it. And so now it's been adopted by companies like red hat, by PayPal, by ByteDance, the TikTok creators. Even Docker is getting on, on board with it.

[Dr. Tamara Nall]

Too. Oh wow. No, that's amazing. And particularly given your background and having developed, you know, so many tools and then seeing that you know, the standards or what have you weren't there. The frames works weren't there. Give me your expertise is amazing. Now tell us about the holy smokes moment. Like what is an example of, you know, a customer or a tester, consumer developer, someone use Joe Zoo and it like changed everything for them in a way that they had not experienced before. Kind of tell us a little bit about that.

[Jesse Williams]

Magic. Yeah, so we've, we've worked with several very secure companies a lot inside of the DOD in different areas. I can't go into too much detail about. But the, the main aha moment typically comes when we show everyone how they're versioning, which there are A lot of great tools out there for versioning parts of the project. And so most people, in their mind, they think I've got all of my bases covered because my data is versioned in something like dbc, which is built for it and it's great for that and my code in GitHub and I might have an S3 bucket happening somewhere or Jupyter notebook. But what they don't realize is that at the end of the day, what they're deploying into production doesn't have a single source of truth. And so when we show them that open source project, Kit Ops, and we say, hey, this is all going to go into one artifact that is tamper proof, it can be cryptographically signed and can push it to our product Josu Hub, that's going to allow your team to work with it and add things that, like inference that are just kind of a headache or the ability to scan these for, you know, any vulnerabilities that might exist. That's where the light bulbs start going off and people start thinking, wow, I can do ML just as easily as I can do a microservices.

[Dr. Tamara Nall]

Application. Got it. So your customers are both government customers and commercial.

[Jesse Williams]

Customers? Yeah, we, we span.

[Dr. Tamara Nall]

Both. Okay, awesome. Got it. Okay, that's good there. And then, you know, our guests are very curious individuals. So if we were to kind of open up the hood and look at the brain of Josu, what would we find? How does it all.

[Jesse Williams]

Work? Yeah, if you were to, to kind of dig into Josu, I guess at the heart of it there would be a registry. So you could kind of think of this as like a typical artifact registry, like ECR or Artifactory or even Docker.

[Dr. Tamara Nall]

Hub.

[Jesse Williams]

Okay. But then we've added all of these things on that are specific to machine learning that you just can't get when you go to the other artifact registries because they weren't built for a Kit Ops model Kit or there's also a CNCF specification that's been built called Model Pack that's based off of Kit Ops as well. And it wasn't built to surface the data that's required for these applications. So really like a single pane of view is. See, now you can dig in a little bit further and kind of go down different routes of.

Things like ease of usage, like the ability to see a diff view like you might see in GitHub of your prompt, which if you recall or if anyone was paying attention to it, there was a malicious pull request that was made to A prompt that went into one of AWS's developer tools that was missed because prompts can be significantly. They can be multiple pages long. You don't have that ability to see, okay, what line actually changed. Then you have, you know, malicious actors doing things they're not supposed to do. We, we make that possible. I mentioned inference. We make it very, very easy to package up a, your model in into like a Docker container with a Llama CPP runtime or Surface Kubernetes YAML that you can just copy and paste right into your config file. So you do a lot of things like that.

And then I also mentioned security scanning. So if you dig into our product, you'll find that there are multiple tools that we've plugged in. Most of them are open source tools, but we've brought them all together to give you one unified view. Thing would be audit logging. This is something that's huge for a lot of companies, especially when they're looking at upcoming AI regulation, to one single source.

Of an audit log of everything that's happened with your models. And like I said, these packages are cryptographically signed, so you can't tamper with the audit. You change it and it's there. And that saves teams massive amounts of time. I mean, we've heard teams that take two developers two to three weeks to create a full audit log of their model and Josie services that.

[Dr. Tamara Nall]

Automatically. Wow. Wow, that's a, that's amazing. Now you gave us an example earlier of how Josu can help, you know, be life changing for a developer, et cetera. We like a second example, but it might be an example where.

As you were going through a next iteration of the product or you were going through the next iteration of development, that it actually gave you chills like, oh my God, like I really created this. My co founders really created this. Tell us about a time where it wowed you the power that JOSU could do and.

[Jesse Williams]

Have. Yeah, I think there's been multiple times where it has, you know, when for me, my background isn't software development.

But the speed at which I was able to package up a model very easily.

There's a popular tool, I'm sure you've heard it mentioned on your podcast, called Hugging Face. The kit CLI allows you to pull in a Hugging Face model packages as a model kit in just one or two commands and just being able to do that is really incredible. But then I told you I was a VP at Docker at one point. Be able to package that then into a Docker container almost automatically and just get your model running right on your computer in just a few seconds. Well, depending on the size of the model, it could take a while, but you understand what I'm saying. Just commands is something that, for me, as someone who's not super technical, I wouldn't have been able to probably do that without Significantly help from ChatGPT or Cloud or something walking.

[Dr. Tamara Nall]

Through.

Exactly. And what I love about what I'm hearing is it's like, you know, it's. It's open source, and it seems like it's very much LLM art tool agnostic.

[Jesse Williams]

Right. You can work with any type of model. It could be a large language model, it could be a vision model. It really doesn't matter because we're not really looking at the type of model. We're looking at the process behind developing the.

[Dr. Tamara Nall]

Model. Awesome. Awesome. And I have to ask this. How did y' all come up with the.

[Jesse Williams]

Name? So Josu is actually Japanese for skilled or tactful. Okay. One of my co founders, Brad, he spent a part of his early career in. In Japan. He was. He was based in a hub over there for one of his companies, and he fell in love with it, and it just kind of stuck with us. And so when he had an opportunity to come up with a name, you know, he went.

[Dr. Tamara Nall]

Back. Yeah, love that. Love that. Joseph. Yeah. My nephew and I went to Japan this past summer. We had a really, really great time. So. Okay, good. I love that. Now, you talked about being able to deploy solutions for the government, private sector, with consumers, et cetera. Talk to me about ethics. Like, given this, the power of this tool, how do y' all think about ethics? How do you. What kind of guard roles do you have in place? Can you elaborate on.

[Jesse Williams]

That? Yeah. So a lot of times when we talk AIML ethics, what we're talking about is what can the. The model underneath do and what can't it do? Look at ethics from a slightly different layer of the development process. So.

We put governance into place so that. Let's say your employees are working on a model. I think there was an example where someone went to a Chevy dealer online and they convinced the LLM chat support to sell them like a new Suburban or something for a dollar. And they convinced the. The GPT that it was legally binding. I don't remember the outcome of that was. But for us, what we would do is we wouldn't actually help it. Not say yes or no to that. We would say is the data that's going into this model.

Violating HIPAA compliance. Right. So they or gdpr. Could someone go onto that model and say, hey, give me the credit card numbers of all of your employees and would it have access to that data? That's the layer where we help is what's actually composing this model and are the things that are composing this model the right things or not? This could go down to licenses. You know, I know that there are countries where certain models can go into production, certain models, you.

[Dr. Tamara Nall]

Know.

[Jesse Williams]

Right. The US has agreements or, you know, there's embargoed nations, things like that that you don't want.

Even sometimes spanning across a company. So when I worked at aws, we had all sorts of different models with all sorts of different data. And you don't necessarily want the, you know, the AWS cloud team, they might be working on the same model as the Prime Video team or the, you know, Amazon Shopping team. You don't necessarily want them seeing what customers are doing inside of each application, though they might have access to the same model to work. Knowing which data and kind of putting in governance and security there is really important. And that's, that's what we focus.

[Dr. Tamara Nall]

On. Right, right. No, I love that focusing on the process.

Is like one of the most important steps when you try to think about like security and ethics, et.

[Jesse Williams]

Cetera.

[Dr. Tamara Nall]

So. Okay, great. So let's talk about the big future for, for Joe Zoo. I used to ask, tell us five years from now, but you know, with AI, the future could be an hour from now. So what do you see as the future for Josu and how it's going to change the.

[Jesse Williams]

World? Yeah, I think we're, we're positioned really, really well for the future. Right now most of the development around AI has been focused on hosted foundation models. So hooking up to the ChatGPT API, we're starting to see a big shift happening where they're using the open source version of those models and they're hosting them on Prem or inside of Cloud. That's what JOSU is made for. We were made for on Prem. And so for us, you know, our ideal future. And I think that there's starting to be a lot of momentum going in that direction. Is actually teams starting to operationalize ML inside of their business. Critical, very kind of secure environments, like the, like the deep operational elements of their business. Not just having a support chat bot or a sales SDR that's, you know, AI, but really like internal.

Really important, really secure data to them. Starting to build those models and doing them in house got it.

[Dr. Tamara Nall]

Perfect. Now, of course, sometimes I do have discussions about, like, on Prem versus not. I mean, what are the disadvantages of being on.

[Jesse Williams]

Prem?

You know, there are. There are disadvantages of being on Prem. I think the biggest one is obviously you're not accessing the Internet in live time.

That doesn't always matter when you're working with owned data coming from things like, let's say you're Iot and you're a manufacturer or logistics company and you don't really care what's happening outside of your environment. You just want to know, where are all my trucks across the industry system in the United States so you can pull that data in.

But really, I think we're seeing that that gap of on Prem versus in the cloud shrinking quite a bit. The biggest disadvantage would be that you would need the developers to maintain that on Prem environment where you don't have someone like AWS or Microsoft to just come in and kind of provide you with all of these tools. You know, you just flip the on switch and all of a sudden you have eventing or a new database or whatever it might.

[Dr. Tamara Nall]

Be. Right, right. Okay. All right, Got it. Now tell us something that we can do today, this week to really experience Joe Zoo in terms of if our listeners want to try, build, explore. How can we do.

[Jesse Williams]

That? Yeah, well, the first thing I would say is go check. Check out Kit Ops, the open source project. It's open source, it's free to use. We've got a great community there. You can get involved with the Discord Channel and that's really the best starting.

[Dr. Tamara Nall]

Place.

[Jesse Williams]

Okay. Once you do that, if you want to try Josu, you can go to Josu ML. We have a hosted sandbox. We don't sell it. It's really just there for people to go and look at it. It's limited feature, but if you think that that's something that would be valuable for your team, reach out and we're happy to spin up POC inside of your environment, whether that's a private cloud or on.

[Dr. Tamara Nall]

Prem. Awesome. Okay, great. Now we always have a question that's called from one genius to another. So. So our previous guest question for you, Jesse, was what memory from your own life would you want to hold on.

[Jesse Williams]

To? Yeah, I was actually, I was telling this one to my kids recently and it was my experience learning how to ride a bike. I had a really big hill, grassy hill behind my house. And I remember the first time that I took off on my bike and I figured out how to balance just long enough to get to the bottom of the hill, and I felt like I was flying. And that's one memory that I wish I could go back and relive just because it's so cool when you're a kid and you feel, yeah, you're doing it for the first.

[Dr. Tamara Nall]

Time. I love that one. I love that one. That is great. Now, could you go back to that hill if you wanted to as an adult and get on a bike and do.

[Jesse Williams]

It? Maybe I'd have to meet the owners of that.

[Dr. Tamara Nall]

House. Okay.

Oh, my gosh. That's a. That is amazing. Being on a bike and then feeling the wind kind of hit up against your face, etc. So, yeah, thanks for taking us there. That's great. All right, so let's do bonus rapid fire. I'll have asked you four questions. You give me the answer that comes straight to your mind. The most overrated AI.

[Jesse Williams]

Trend. Ooh. I'm going to have to say the 9, 96 culture inside of AI.

[Dr. Tamara Nall]

Startups. Okay, no, tell.

[Jesse Williams]

Us. Okay. Working nine to nine, six days a.

[Dr. Tamara Nall]

Week.

[Jesse Williams]

Okay. Not a fan of it. I think you get most of your creativity outside of the workplace, so work hard nine to five, put 40 hours in and you'll be good and do.

[Dr. Tamara Nall]

The. And so people actually are walking around saying996. Like, they're like.

[Jesse Williams]

Vibing. Yeah, you can search it on.

[Dr. Tamara Nall]

LinkedIn. Okay. All right, then. Okay, what's the most underhyped tech or AI.

[Jesse Williams]

Trend? Ooh, the most underhyped tech or AI trend. Right now, I'm going to say.

Custom GPTs. I think a lot of people don't take the time to really train a GPT for a specific skill. But when you do, when you know it can take two or three hours to get everything in there, but once you upload the documents to it and it really understands a specific task, it can be quite powerful. So I think that's right now, the most underrated thing that you could.

[Dr. Tamara Nall]

Do. Okay, awesome. What's a book we should all.

[Jesse Williams]

Read?

I'm gonna say, you know, it's a classic one. It's Hackers and Painters by Paul Graham. It's a little bit dated, but I love the way that he thinks the Future. It's one of my favorite books just to go back. And it's al. It's also just a beautiful book, the way that it's.

[Dr. Tamara Nall]

Written. Okay. Hackers and Painters. Y' all heard it here. And then what about your biggest, boldest AI.

[Jesse Williams]

Prediction? My biggest, boldest AI prediction? I think AI predictions typically go in one or two directions. The first one is AI is going to take everything and no one's going to have a job. I actually fall on the other side of that. I think that AI is going to open up the opportunity for everyone to basically be their own entrepreneur if they want to. We're on the cusp of seeing, you know, our first billion dollar, 10 person company. But I really think for people, especially if you're, you know, a side hustler, AI can be incredible. Just the amount that it allows you to do all by yourself. And so I think it's actually going to open up more opportunities for people.

Is going to take.

[Dr. Tamara Nall]

Opportunities. Yeah, yeah, I often talk about that with folks. I love that AI kind of levels the playing field. I mean, you can take, you know, some young youth or kids somewhere that doesn't have resources or access and now they have, you know, AI and now they're at a level playing field with someone that has a lot more resources and, you know, the intellect into development or creating, etc. Is there now because of AI. So I'm with you. I'm definitely with you on that. So, Jesse, I've loved this conversation. Tell us, how can we get in contact with you? Tell us again, if we wanted to play around with Josu, how do we do that and what we can.

[Jesse Williams]

Expect? Yeah, absolutely. So the easiest way to get in touch with me, if you want to talk more about AIML or get a demo, reach out to me directly on LinkedIn. Jesse Williams. Jesse Williams. Very easy as far as getting started with the product. Like I said, Kit Ops, which is KitOps.org go learn about it, check it out. We've got a vibrant discord community. We'll also be at qcon North America coming up in November, so you can stop by the booth and chat with us there. And for josu, check out Jozu.com you can learn all about the poll product and what we've built on top of Kit Ops. And check out the sandboxy ML. There are links there on Josie.com to that as well. But yeah, we'd love to, love to hear you. And yeah, if you want to just reach out directly on email, it's just.

[Dr. Tamara Nall]

Jessezu. I love that. Jessezu.com all right, amazing. Well, again, Jesse, we are a great podcast because of wonderful guests like you. So thank you for spending time with us telling us about Josu and all the wonderful things that y' all are doing. Your amazing background, your amazing bicycle in the wind story, as well as your passion about being a dad. So we just love learning about you and the company and can't wait to hear all the great things that you're going to do and the company will do to change the.

[Jesse Williams]

World. Awesome. Well, thank you so much.

[Dr. Tamara Nall]

Tamara. Absolutely. All right, everyone, until next time.

Lee with AI thanks for tuning in to lead with AI I'll see you next time as we continue exploring the cutting edge innovations shaping AI across the public and private sectors. Until then, keep leading with AI.