How Lyzr AI Reached $12M ARR at 95% Gross Margin with 32 Enterprise Customers (Interview with CEO Siva Surendira)

Opening: Lyzr's growth and 95% gross margin

Siva Surendira

00:00Why is Lyzr growing really fast? We are a sovereign, full stack agent platform that enterprises could run locally within their own cloud or even on premise system. We kind of replaced 20 different individual technologies under one single homogeneous platform. We closed Q2 this twenty twenty six at 12,000,000 ARR. So we grew by 20x in the last nine months. We are projected to get to 30,000,000 minimum by end of the year. And, Nathan, we are operating at

00:3295% gross margin.

Host intro and guest background

Nathan Latka

00:36Hey, folks. My guest today is Siva Surendira. He's the CEO of Lyzr, a two time founder, previously built Power Up Cloud, an AWS consulting firm, which was acquired in 2019, where he then ran the AWS business group globally. Today, Lyzr builds enterprise infrastructure for deploying and governing AI agents, pursuing a vision it calls organizational general intelligence. Siva, you ready to take us to the top?

Siva Surendira

01:00Absolutely. Nice to meet you.

Nathan Latka

01:02It's good to have you on, and we were talking before the show. You know what to expect. It sounds like you you caught some early episodes back in the day.

Siva Surendira

01:08Absolutely. I mean, I've been... Like I mentioned earlier, I'm a big fan and lot of during the early stages of building Lyzr, a lot of the videos that you did was extremely helpful, kind of reaffirmed the confidence that a founder needs, to be honest.

Origin story: idea behind Lyzr

Nathan Latka

01:24Where did you come up with the idea for this?

Siva Surendira

01:26So after I sold my previous startup to this large, global system integrator...

Nathan Latka

01:31Which one?

Siva Surendira

01:32I sold Power Up Cloud. This is the company that I built and ran, and, it was, an all cash deal, which is good for me and the whole team, and we sold it. And I moved to The US as part of the sale in 2020. And I was leading this global AWS business unit at LTI, which was doing $65,000,000 when I took over, the whole business unit. And I took it to about $220,000,000 in under two

02:00and a half years. So I did about $400,000,000 for the business unit in three years. And during that time, I used to go into these QBRs with Excel sheets, spreadsheets and pivot tables and only for the leaders to ask a lot of questions which I'm not prepared at all. I mean I know my business really well but the line of questioning was very different from the management team. And so when my time was up at LTI,

02:27which is when my golden handcuffs came off, I wanted to come back to building startups. And the timing was perfect because that's when we had the GPT 3.5 API come out. So I obviously as a big data engineer and I realized, okay, what if we address the problem that I faced? What if we build an AI data analyst that can not only analyze your spreadsheets, but also can prepare you with all these questions and ideas that

02:57you may have so that you can understand the data really well. That was the whole thought process. And when I spoke to a lot of these vice presidents in large services firms and banks, I realized that all them all these folks are on the same boat. None of them have business analysts or dedicated EAs who does the work for them, which is exactly where AI can play a massive role. While building it, I realized that there

03:23is a bigger problem to solve because even as a solo developer, I found it very hard to deploy and manage all these open source packages. And for enterprise, it would definitely be a nightmare. So that insight led to pivot, in the first three months of starting Lyzr to, becoming an enterprise framework and platform, allowing enterprises to build AI systems and agents.

First line of code and founding team

Nathan Latka

03:49What year did you write the first line of code for the platform?

Siva Surendira

03:53April 2023.

Nathan Latka

03:54When founders come to, you know, Founderpath to raise from our fund, I go, okay. If it's a solo founder, great. They can move fast. They can break things. They don't have to get seven people to agree. I'm reading here from my research team. Cofounders include Jiffin, Ankit, Anuroda, and then you. Is there four of you? And how do you agree? How'd you split equity on day one? This is a lot of people.

Siva Surendira

04:13I start alone. Then I start building something. And I have some interns who might probably... I might hire to build something. I get to a stage where I am convinced that okay, there is some potential here and then I start building the team together. So Jimmy and this is Jithin and Ani were introduced to me. Ani, I knew Ani earlier as well And Jimmy was introduced to me and we started speaking with one another. And they

04:40came on board in around January 2024, almost six months into the system. And then we had Shreyas and Kush, who also are founding architects, who came on board. This is the core team, five of us, of which four of them can code and he is our growth expert. So that is how the whole team came together. At least that's my style. It's not that I need a co founder to start something. You just need an idea.

AI SDR experiment: zero to $4M contracted ARR in three months

Nathan Latka

05:05What did you finish at the end of twenty twenty four with in terms of revenue? Do you remember

Siva Surendira

05:05We

05:11finished 2024 at zero revenue, right? But this is what happened. 2023 is when we started building something. 2024 is when we started doing some early experiments and you won't believe during that experiment, around July 2024, we built an AI SDR as an open source agent on our framework. The idea was to show that, hey, you can have AI SDR completely open source. And during that time, 11x and Artisan were two popular AI SDR companies that I

05:47think Andreessen Horowitz invested $80,000,000 or something in 11x, right. So

05:52my thesis was that, okay, why should you pay so much for an AI SDR if you could build it as an open source agent on Lyzr framework? And interestingly, we started getting a lot of demand for what we built.

Nathan Latka

06:05What was the name of the open source project?

Siva Surendira

06:07Jazon, j a z o n.

Nathan Latka

06:10A lot of people say, Nathan, where's the crop of the fastest growing startups coming from? And I just think if you put a scraper together to track GitHub stars on these open source products, that's a great leading indicator if something's got legs or not.

Siva Surendira

06:22We went from zero to 4,000,000 in contracted ARR in three months. Just three months. Now why contracted? Because we told our customers that very honestly that, hey, we don't know whether it will work, but sign up with us and we'll work with AWS to even fund the internal pilot and AWS has a plan to fund these pilots. We said, we will try and do this for you and if it works, you convert into a paying customer.

06:49So that is why it's a contracted ARR. They started with a contract. The first three months was covered by AWS and the rest nine months by the customer. This is the business model that allowed us to show the product really well and then we were able to convert a lot of customers who came on board. This was the bull run that AI SDR companies had.

Nathan Latka

07:11How did you get that initial tranche of like 10, 15 customers? Did it come from the ones that were like starring the open source project or somewhere else?

Siva Surendira

07:19So we started seeding on Twitter and LinkedIn and Reddit highlighting that you have an open source version that is available that you could try. You don't have to necessarily spend. I think 11x was back then charging $70,000 to $100,000 per year for a plan. And then Ani who's my Co Founder and Head of Growth, he's fantastic. His team was able to then get the SEO in play and we started getting 400 inbound leads a month and

07:47we had a 60% demo conversion rate. So that is the bull run that we had in 2024, right. And we went to 4,000,000 ARR, contracted ARR by

Shutting down the AI SDR and pivoting back to core platform

Siva Surendira

07:59September. Only in October, we said we're not going to do this anymore and we stopped doing it because we realized that AI SDRs don't work. The promise of AI SDRs and Nathan you would know this really well. The promise was that it is supposed to book meetings for you. It is supposed to write emails automatically book meetings for you. The moment that promise was broken customers felt that okay, you know what, this tech is not working.

08:27That's exactly what we saw from close quarters. The other SaaS companies were not admitting it but we saw that, okay, you know what, AI SDRs can probably do mass emailing, but can it book a meeting for you? That depends on many other things. What we did, we gave the open source option to all our customers who had already signed up and, we just discontinued the AI SDR to go back to the core product, which is the agent

08:52framework itself.

Nathan Latka

08:54So Siva, what is your prediction for all these AI SDR agents since you built your own, grew it to $4,000,000 of revenue, then shut it down? I mean does 11x and Victor and Finn, do they have, you know, Artisan, do they eventually have churn problems and shut down? Or what's your prediction?

Siva Surendira

09:06Massive churn problem. It works if you are trying to just send mass emails. The moment you start expecting AI SDRs to book meetings for you, that's when it falls flat.

Nathan Latka

09:17Even the mass emailing, how are people setting up their email architecture to make sure they have warm inboxes to make sure they show up in the primary inbox of the Fortune 200 brand that they're targeting? I mean even getting that to work is not easy.

Siva Surendira

09:28It's not easy. Options are like buy 30 to 40 domains on Lemlist or Instantly, then start scheduling, use the API to integrate an agent or cloud directly. It's probably the lowest cost when it comes to marketing, which is landing in an inbox. If your agent could write a really good opening email, I think you would have caught the attention of the ICP. Over a period of time, what we realized was do not try and do the

09:59seven email drip campaign stuff, etc. Try two emails. Hit the point. Give them the links and screenshots to decide. If they don't decide in two emails, they're not going to decide in seven emails. October 2024 is when we shut down the AI SDR product. We went back to our drawing board which is, hey, we wanted to be an enterprise agent company. Let's do that. And we took three more months to build out the Developer Studio. And January

10:262025 is when we launched the Lyzr Agent Studio, which is a low code, no code builder platform for developers. That eventually turned out to be a good decision for us.

Agent Studio launch and first 25 customers at $10K plan

Nathan Latka

10:36Okay, so new launch in January 2025. Did you get your first 10 customers? What were you charging?

Siva Surendira

10:42Again, good question. So we started with a $10,000 annual plan. Q1, we onboarded 25 customers, mostly startups and SMBs, and we went to $250K in ARR by Q1, right. And then by Q3, we launched a $50,000 plan and a $100,000 plan. By Q3, we went to $650K in ARR. That is when we signed our term sheet with Rocketship who led our Series A. Accenture Ventures participated. But what happened after that is the growth story,

11:16right? Q3 2025, $650K ARR. And we closed Q2 this season, this 2026 at 12,000,000 ARR. So we grew by 20x in the last nine months. We are projected to get to 30,000,000 minimum by end of the year. But there is one large government deal, if that comes in, we'll get to $50,000,000 by end of the year.

Largest customer and why enterprises choose sovereign AI

Nathan Latka

11:38What's your largest customer pay you today?

Siva Surendira

11:40It is a federal agency close to $2,000,000 Why is Lyzr growing really fast? We are a sovereign full stack agent platform that enterprises could run locally within their own cloud or even on premise system. That is what we are. So today companies are understanding what OpenAI and Anthropic are doing. They are obviously charging you for tokens but eventually they're able to take all the intelligence away from you. If you're an insurance firm, the moment you upload

12:14your underwriting handbook to OpenAI or Anthropic, it's gone. The intelligence is now with them. They can share the same decision making to every other insurance firm in the world. Your secret sauce just went out. So this is something that enterprises are realising very quickly. So they are looking at full stack sovereign platforms like us, which they could deploy with their own cloud or even on prem systems so that they can really own the intelligence. So that

12:43is what is resulting in our growth. Lyzr is full stack which means all the necessary building blocks that you need for a complex agentic system are available within our single platform. We kind of replaced 20 different individual technologies under one single homogeneous platform, which is why we had Accenture invest in us twice in six months and they are the world's largest IT services provider.

Lyzr Optimus: the on-premises AI appliance

Nathan Latka

13:09As someone watching this is a founder of a $10,000,000 ARR company. I'm going, yeah, I wanna keep my alpha and my intelligence with me, but how do I... Like, do I have to... If I think back to like the the Rackspace days, do I have to have a closet on my business with a bunch of HP 200, you know, an H200s running or Blackwells running and then put your application layer on top of it? Like, what's

13:28the infrastructure under it? How do I get the compute power if I use your application?

Siva Surendira

13:32It is

13:33going to be a combination, Nathan. It is going to be an on prem appliance which has H200s, H100s or AMD chips. So that is your on prem appliance completely cut off from internet. But you can your CFO office, your R and D team, your say biotech team could use it for local intelligence to build agents and automate a lot of work. Which is why just last week we launched Lyzr Optimus which is an on prem appliance

13:59that you can buy from us. It can support up to 10,000 concurrent users. You won't find that on the platform yet because we just started pre orders for our existing clients. So 20 percentage of any enterprise workload will run with local hardware and about next 50% will be on one of their hyperscaler platforms like Amazon or Azure or Google and they will be using models that these hyperscaler platforms provide or they will be using open source

14:26models behind bedrocks of the world, which is semi data sensitive. And the rest 20% is where or 30% is where they will be open to sharing with OpenAI or Anthropic directly.

Nathan Latka

14:38So let me ask you a follow-up on this Cause my audience is a combination of tech people that are following everything you're saying and people that are not tech and they might get lost. And that's sort of me. So if they think literally about, okay, I wanna own my intelligence. Are they going on eBay and buying for $40,000, you know, 10 H200s and then putting in a closet and then putting your app on top

14:56of it and running it? Or are they renting GPU space from a middleman somewhere and then putting your intelligence on top of your application layer on top of it?

Siva Surendira

15:03Three options, right. The option that is on fire right now is the inference providers. Together AI, Fireworks and Baseten. These companies are inference providers. They give you open source models and you can fine tune so you don't have to buy hardware. And these companies ensure data privacy. They are not the big labs like OpenAI or Anthropic who uses your data to retrain something. Their job is straightforward. They will host an open source model like a

15:33DeepSeek for example or a GLM or a Qwen and then they give you inference capability.

Nathan Latka

15:39Wen, what makes their business model hard? Or is it easy to copy? You just have to go rent GPU space from the hyperscalers and then rent it out at a higher rate?

Siva Surendira

15:47Sometimes they rent, some... And mostly they buy. So it's all about demand. So two things. One, do you have enough hardware capacity? And number two, do you have a really, I would say, optimized software stack? The reason why Together, Baseten and Fireworks are good is because their software stack is very strong, which is why if you are an individual, you don't have to buy these NVIDIA H200s yourself. You can rent it out from these inference providers.

16:17Option number two, big hyperscalers like AWS, Azure and Google, they also have some capacity. CoreWeave, all the Neo Cloud, right? CoreWeave, NBS, they also have these options. Then option number three is buying hardware appliance from companies like us. This is Lyzr Optimus, an on prem agent factory for enterprises and teams who wants to own their intelligence, right. It comes with, it can support up to 10,000 concurrent users, which means even a large bank can adopt this.

16:4795% lower cost compared to a frontier API usage like GPT 5.5s of the world. It just takes thirty minutes to set up and get started.

Pricing tiers from $10K to $1M and platform demo

Nathan Latka

16:56What are you going to sell this for?

Siva Surendira

16:58So there are four configurations that we are launching. Optimus Personal is for the CXOs. Imagine a CEO or a CFO who wants to have a device on their desk. So there is Optimus Personal. Starts at $10,000 Optimus Max, is $1,000,000 It comes with eight, small models, two medium models, two large models, one OCR model, and one voice model. It can support up to 10,000 users.

Nathan Latka

17:23What's the difference between your Optimus personal plan at 10 k versus like what most people are doing now which is like stacking Mac Studios for 3 k a pop?

Siva Surendira

17:30It is not just the hardware that you get. What you also get is the software. Right? This is what you get. The whole studio.

Nathan Latka

17:38Wait, tell. Okay, so this is great. I love a visual. So just to be clear, this is like what a paying customer would see. We're now logged into your platform.

Siva Surendira

17:44Yes. You get an end to end Studio where all the agents that you are building across are sorry are registered here. You have an option to create a task agent or a voice agent or even a workflow or even bring third party agents via proxy agent. You are able to build complex multi agent systems through the studio.

32 enterprise customers and 80,000 free builders

Nathan Latka

18:06How many customers are you serving today?

Siva Surendira

18:09Today, 32 very large enterprise customers. Like I said, the deal values are between $250,000 to $1,000,000 and one customer obviously closer to $2,000,000 And we have 80,000 builders on the platform. You can go to Studio today, create a free account, you get 500 credits, and you can start building agents yourself.

Nathan Latka

18:29Why would they build on you versus going directly to Zapier, N8N, or all these other agent building tools?

Siva Surendira

18:35Lyzr has 50% more agent building blocks or modules compared to what even some of the best or top agent platforms in the market have today. So it is a comprehensiveness of what we bring to the table, allows us to obviously help our enterprise customers build really complex systems. This is a developer studio, right, built for developers. We then wanted to build something for business users which is why we built architect.new. So this is something that

19:02I would encourage the users to try. This is purely built for business users. It is not just an app builder but an agent builder primarily. So architect goes out and plans in detail the kind of agent that you want to build. It then visually builds the agent for you writing the prompts, selecting the models automatically. Then it also builds the app for you. All three in one shot.

Nathan Latka

19:24The argument, that you're making is, hey, you build the agents inside of here it's your own data, it's private, you're not passing your business intelligence to the foundation models who then might distribute it to every other law firm on earth.

Siva Surendira

19:34That's correct.

$8M Series A at a $50M valuation on $650K ARR

Nathan Latka

19:35September 2025, you hit $650,000 of ARR, and you did an $8,000,000 Series A. Right?

Siva Surendira

19:40That's correct.

Nathan Latka

19:41Are you comfortable sharing the valuation?

Siva Surendira

19:44Yeah. We did it 50,000,000 valuation.

Nathan Latka

19:46So, I mean, how did you think about the multiple then? Mean, look, I mean, obviously, you wanna get the highest multiple possible, but you've been through this before. You know raising at a high multiple can sometimes hurt you.

Siva Surendira

19:53Yeah. Yeah. And also, I'm not a Bay Area Founder. I'm a New York Founder, and I'm an immigrant, so I didn't have any network. So raising the first round was pretty hard, to be honest. In spite of my previous success that I had, we had to raise purely on our ARR growth. So it became just a multiple of whatever ARR was.

Nathan Latka

20:11That's a 76x ARR multiple, right, on six fifty ks of ARR?

Series A plus at $250M valuation four months later

Siva Surendira

20:15Because we had a good pipeline. But here's one interesting thing, right? This is October. In February, we did our Series A plus at $250,000,000 valuation. Our valuation jumped five times in a matter of four months.

Nathan Latka

20:29What was revenue in February this year?

Siva Surendira

20:32In February, when we raised that round, was $3,500,000

Nathan Latka

20:32So

20:37you've gone from $3,500,000 of ARR in February 2026 to June, 12,000,000 of ARR. So in three, four months, you more than almost trip... More than tripled revenue.

Siva Surendira

20:47Yeah. And in July, we will be at 15, and we are targeting 30 by end of the year.

Nathan Latka

20:51You're still trading at a 70 x revenue multiple.

20:54I mean,

20:54but your growth, you'd argue the growth justifies it.

Siva Surendira

20:56That's correct. And and, Nathan, we are operating at 95% gross margin.

Nathan Latka

21:01What about net net margin? Are you profitable or burning today?

Siva Surendira

21:05We will break even in thirty days.

Nathan Latka

21:07Okay. If you wanted to. I imagine you're not. You're gonna keep burning to grow.

Siva Surendira

21:11Exactly. Exactly. Exactly.

Nathan Latka

21:12That hardware you just showed me, the most expensive one for a million bucks, what will your cost of goods sold beyond that based off the manufacturer or the chips you're putting inside it, etcetera?

Siva Surendira

21:20I think just the hardware BOM alone is 50%, 48 to 50%.

Nathan Latka

21:25So you're reverse engineering to get like a 48% hardware margin, and then you'll upsell obviously 95% margin, a software and application layer on top of it.

Siva Surendira

21:32Exactly. Because the real value is the software. Right?

Total raised, Series B talks and growth through system integrators

Nathan Latka

21:34So how much total have you raised to date?

Siva Surendira

21:3614.5. And we are now in talks to do our Series B. It's a 100,000,000 round.

Nathan Latka

21:40So you're like growth at all costs, basically. What's the fastest way to... Do you go through inorganic growth, buy a bunch of companies in your space just to buy your way to a 100,000,000 of ARR, or just keep doing what you're doing, grow organically?

Siva Surendira

21:50I have a different take on inorganic growth. We have several other system integrators investing in Lyzr and also partnering with us because we help them ship agents that can go to production for their end customer. So that is inorganic growth for us, right? If you make your partner win, they will take care of building the pipeline for you, bringing in the demand.

Winning against Palantir and the $400M acquisition question

Nathan Latka

22:11What I'm trying to wrap my head around is when you're going head to head with Palantir on a deal and the US government is the buyer, how are you winning these $2,000,000 contracts, right? People are thinking Palantir, they raised a bunch, they're worth billions of dollars. Why would they give, you know, respectfully, right, your little startup a shot?

Siva Surendira

22:29Exactly. I think that is the underdog tag that gives us the advantage both in two deals both Palantir and the other large enterprise which is a critical infrastructure for The US who I cannot name. The first one is the US government themselves. Both deals were Palantir compete. We were able to win number one because of the product superiority because the product is agent first, right. We didn't have a baggage of ontology and all the other previous

22:55softwares to sell. We just had one focus which is how do I build agentic systems that can go production. So that is the focus. I think that product superiority helped us win. The second one is we were able to ship a prototype in ten days to our customer. It's always been a dogfight, Nathan, to be honest. Like almost all the large deals that we won, we were pegged against either a Palantir or an Agent Bricks or one

23:21of these or LangChains of the world. It is always one of these dogfights that we have to win.

Nathan Latka

23:26If one of those firms approached you today and offered to buy the whole business for $400,000,000 all cash upfront, do you take the deal?

Siva Surendira

23:33They can't afford us. But yeah, we are currently raising a $100,000,000 round and you could probably guess the valuation that we are moving towards.

23:42Which is where

Nathan Latka

23:42No, So I can't. What valuation are you targeting?

Siva Surendira

23:45Let the market sit. It's too early right now, so

Nathan Latka

23:47How much revenue ARR do you think you'll add in this month?

Siva Surendira

23:51We have a Q3 target of $20,000,000 Q4 and Q1, we grew 300% quarter on quarter. Q two, we grew 200% quarter on quarter. And obviously, as the number grows up, the percentage comes down. So this quarter, we'll probably grow 80%.

Nathan Latka

23:51So is

24:06it fair to say you're adding 1 to 3,000,000 of new ARR per month?

Siva Surendira

24:09Yes.

Nathan Latka

24:09Listen.

24:10On that note, if people wanna follow your story, Siva, where can they find you online?

Siva Surendira

24:15I'm... LinkedIn is the best place. You can find me, Siva Surendira, Lyzr. I'm on LinkedIn.

Nathan Latka

24:22Guys, there you have it. Started in 2008 as a big data engineer at Tesco in Bangalore, and look at him now. Siva, thank you for taking us to the top.

Siva Surendira

24:30Thanks, Nathan. Thanks for having me.

Nathan Latka

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