Kibo Commerce: How Agentic AI is redefining scale, simplicity, and speed in ecommerce

Ram Venkataraman: The next step as CEOs is how do you scale this company and then double it without adding the same number of people that you had in the past?

Ram Venkataraman: Or you're thinking about other companies growing to the next level. How do you add more capabilities in the business without adding more people?

Ram Venkataraman: So can you do more with less in post-sales? Can you do more with less in go-to-markets?

Ram Venkataraman: So AI is a critical part of scaling because the next generation companies, for everybody in our shoes, are gonna come with a completely different cost structure than where we are.

Kailin Noivo: In this very interesting conversation with Ram, the CEO of Kibo Commerce, we got into a lot of really cool topics.

Kailin Noivo: One being, what it's like to be owned by a private equity group that wants you to build a lot of different products, how they're thinking about agentic commerce and really what that means, and how more importantly than anything else, they're creating value for their merchants.

Kailin Noivo: So really excited for you folks to hear this one.

Kailin Noivo: Welcome to another episode of the Ecommerce Toolbox.

Kailin Noivo: Joining us today, we have Ram who's the CEO of Kibo Commerce.

Kailin Noivo: Kibo has some really interesting customers like Zwilling, Ace Hardware, Coastal Construction.

Kailin Noivo: So really, really excited to have Ram on the podcast today. Welcome.

Ram Venkataraman: Thank you, Kailin.

Ram Venkataraman: Thank you for having me on the podcast.

Kailin Noivo: Awesome.

Kailin Noivo: So I'm gonna ask you a question that I'm assuming your board and your investors are asking.

Kailin Noivo: What's your AI strategy?

Ram Venkataraman: A multi-pronged story when it comes to AI for us at Kibo as much as, you know, a lot of people started off with AI as a feature, we're kind of thinking about it as a foundational enabler, not only for the commerce experience, but also from a company perspective. Right?

Ram Venkataraman: So I think of it in, you know, three different ways. One is, obviously, we have introduced a lot of capabilities.

Ram Venkataraman: We're probably first out of the gates.

Ram Venkataraman: In March at ShopTalk, we launched our agentic commerce framework and our first agent and then, in May at our show at KiwiConnect, we launched, you know, our first set of beta customers using the capability.

Ram Venkataraman: So we call it Engage, Configure, Explain, and Tune.

Ram Venkataraman: These are four types of agents. Engage is a pre-purchase, post-purchase conversational agent that runs on brands' websites.

Ram Venkataraman: Everything is powered through Google Gemini's model capabilities.

Ram Venkataraman: The other parts, Configure and Explain, work inside the platform.

Ram Venkataraman: So, Configure allows people through a conversational approach to configure a promotion or configure an order orchestration or any anything that you can, kind of, configure much more easily to do that versus learning 50 clicks.

Ram Venkataraman: All our platforms are fairly complex, you know, and setting up a promotion is a fairly complex experience there.

Ram Venkataraman: So Configure allows you to do that. Explain is, you know, we all run into this stuff, hey, what happened to this specific order?

Ram Venkataraman: Why did this promotion run?

Ram Venkataraman: So turn all the logs, turn all the rules back again in a very english-like experience for somebody to say, hey, this order went to this store or this warehouse because of blah blah blah reasons, and so the inventory position, so on and so forth. Right?

Ram Venkataraman: And then Tune is basically our approach to really lower the cost of running the platform where the system performs operations on its own.

Ram Venkataraman: So we're trying to go from this in a system of record mode where, you know, we've had these rules and screens, and workflow set up for the system to automatically tune itself.

Ram Venkataraman: So, this is kind of the first product-oriented approach, obviously, since then, you know, MCP is a big thing on that front.

Ram Venkataraman: We have launched MCP capabilities in our platform now. So at a product level, it's a little bit more, hey, it's not a feature.

Ram Venkataraman: It's a core thing in the system. But then the business has also evolved significantly.

Ram Venkataraman: So the next step as CEOs is how do you scale this company and then double it without adding the same number of people that you had in the past?

Ram Venkataraman: Or you're thinking about other companies growing to the next level.

Ram Venkataraman: How do you add more capabilities in the business without adding more people? So can you do more with less in post-sales?

Ram Venkataraman: Can you do more with less in go-to-markets?

Ram Venkataraman: So AI is a critical part of scaling because the next generation companies, for everybody in our shoes, are gonna come with a completely different cost structure than where we are.

Ram Venkataraman: And the final thing I would say is how do you use AI to deliver innovation faster?

Ram Venkataraman: So this year, we launched a whole dropship platform that sits next to our OMS very heavily engineered through AI approaches.

Ram Venkataraman: So, you know, I think I have a point of view that I think maybe very focused approach in SaaS companies really thinking I'm gonna do five things and five things very well may go away in the next two to three years because the cost of writing new software is going down so fantastically quick these days.

Ram Venkataraman: So I think there's a lot to unpack in the AI world. It's obviously one for our customers that's very important.

Ram Venkataraman: And how do you lower their cost of ownership?

Ram Venkataraman: How do you help them scale, but also inside the company?

Ram Venkataraman: It's gotta be a core thing every single day.

Ram Venkataraman: So when we talk at the board level, those are the things I'm focused on.

Ram Venkataraman: How do I help my clients? And how do I scale faster?

Kailin Noivo: Great answer.

Kailin Noivo: And, you know, I skipped a question I usually like to start with.

Kailin Noivo: How did you get to your role?

Ram Venkataraman: Oh, that's great. Yeah. I am a product and technology guy by training and by background.

Ram Venkataraman: So I started my career as an engineer way back when I think my, if I tell you my age, I'd probably date myself.

Ram Venkataraman: So I've been in the industry for a long time in lots of different verticals.

Ram Venkataraman: Commerce is probably a new vertical for me. I've been here probably seven years.

Ram Venkataraman: I came to the ranks, worked in lots of different industries, you know, fintech, hospitality, worked in payments before I came here and then I joined Kibo as a Chief Product and Technology Officer in 2018.

Ram Venkataraman: And then, obviously, we went through a divestiture of certain capabilities that we had personalization.

Ram Venkataraman: We had acquired companies called Monetate and Certona. When we divested that late in 2022, the board asked me if I wanted to be the CEO, so, obviously, first time CEO.

Ram Venkataraman: Now, like all human beings, we all go through imposter syndromes, you know, there's always doubt in our mind, can we do this?

Ram Venkataraman: But I'm one of those people who believes in, you know, when you get an opportunity, take it and then figure it out.

Ram Venkataraman: And so, you know, obviously been in this role for almost three years but, you know, I think this is the right time for technology-backed CEOs.

Ram Venkataraman: The market's evolving so fast especially with anything that is gonna be around agentic. Agentic commerce is just one thing that we talked about.

Ram Venkataraman: There's lots of things that are evolving, and companies are gonna evolve and, you know, I feel like I'm in the right place at the right time here at Kibo.

Kailin Noivo: No. That's really cool and maybe a very Kibo-specific question.

Kailin Noivo: So we have some mutual customers, but I'm always curious, like, where do you guys think you have kind of the right to win, and what segment of the market do you feel like you're best in?

Ram Venkataraman: Yeah. Fantastic question. Right?

Ram Venkataraman: So when we think about an ideal customer profile, we all have ideal customer profiles in terms of how we think.

Ram Venkataraman: So maybe I'll, you know, for your audience, tell you a little bit about what Keyword does, right?

Ram Venkataraman: I think our core value proposition for businesses is to unify their operations across all channels. That's really our core north star in terms of simplifying complex business models. So we look for businesses that are fairly complicated.

Ram Venkataraman: So define complexity. Everybody defines complexity in different ways.

Ram Venkataraman: So for us, complexity comes from the notion of lots of inventory locations, right?

Ram Venkataraman: So we provide three capabilities in a unified and yet very composable platform, ecommerce, order management, and subscriptions.

Ram Venkataraman: All of these are core parts of the capabilities that we provide, and these are very composable.

Ram Venkataraman: We are part of the Mach Alliance, so customers can choose to buy bits and pieces of it or all of it, or certain microservices some customers may buy, just cart and check out from us, or, you know, promising on inventory availability services, so on and so forth, right?

Ram Venkataraman: So when we think about our ICP, we're looking for complex businesses. Right?

Ram Venkataraman: So businesses' complexity comes from two or three things: inventory locations and inventory locations could be stores or warehouses or distribution centers or drop shippers, how they design different inventory locations that they have.

Ram Venkataraman: The complexity of SKU catalog is an important aspect for us in terms of, hey, how many SKUs do you have?

Ram Venkataraman: You know, if it's a thousand SKUs, it probably is too simple for us. You know, we're looking for large businesses, whether it's B2B or B2B, right?

Ram Venkataraman: We have distributors as part of our customer base that are large retailers in our customer base as we think about.

Ram Venkataraman: And there are some DDC vendors who are also fairly complex in terms of how they think about it. Right?

Ram Venkataraman: So complexity comes from inventory location, it comes from SKU catalog, and there are certain industries.

Ram Venkataraman: Some hard goods industries, like whether it's home hardware, whether it's medical supplies, whether it's machinery products, those are better suited for us.

Ram Venkataraman: So those are the things that we focus on, and we get into the market, think, from our order management perspective.

Ram Venkataraman: So being running on the same platform, it's a land and expand strategy for us in terms of go-to-market perspective.

Ram Venkataraman: We know our core differentiation in this market is through our order management capabilities, but then when customers see that, they also buy our ecommerce capability.

Ram Venkataraman: So customers like Ace Hardware run ecommerce and OMS on Kibo's platform, customers like Al-Futtaim Group in The Middle East, they run on our platform.

Ram Venkataraman: So lots of customers who run more things over a period of time and so, we've seriously lowered their total cost of ownership and improved the ROIs significantly because a lot of this, you know this, you've been in this space long enough.

Ram Venkataraman: Integrations are a big, big pain in the rear end in terms of how customers have to maintain these complex ecosystems.

Ram Venkataraman: We simplify that by providing more capabilities out of the box.

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Kailin Noivo: Obviously, composable commerce is gaining a lot of traction, but in some cases, there's kinda like, maybe confusion is not the right word, but there's almost, like, too many choices for merchants.

Kailin Noivo: How are you guys thinking about strategizing, like, what's your strategy to basically offset some of the complexity and actually see that customers don't get overwhelmed and potentially flip to the other direction and say, hey, let's prioritize simplicity?

Ram Venkataraman: Yeah. So I think that's one of the key things. Right?

Ram Venkataraman: I think as much as composable is important, decomposable is also equally important. Right?

Ram Venkataraman: So, you know, we've been through this journey.

Ram Venkataraman: Like I said, I've been in this industry for seven or eight years now, and I've seen this wave of the, in the last part of the ATG, web sphere commerce space, then to the Salesforce world, then to composable, now in the Shopify space.

Ram Venkataraman: And then the industry keeps going back and forth in terms of how it thinks about it.

Ram Venkataraman: And it's largely because, you know, the monolithic suites were not composable and, you know, they were not decomposable.

Ram Venkataraman: You had to completely replatform all of those things from end-to-end because they provided a lot of capabilities but didn't have the architectural flexibility.

Ram Venkataraman: And then we went fully composable, and,you know, every vendor provided a point solution and you had to bring all this together.

Ram Venkataraman: Where we come into the market is, we have a lot of capabilities out of the box that clients can buy and, you know, one of the core things is that we've tried to really strive to find that Goldilocks position between business productivity and developer flexibility.

Ram Venkataraman: A lot of the cost of the composable platforms are built for developers. You know, we really strive hard, being part of the Mach Alliance.

Ram Venkataraman: Obviously, we feel really good about our developer flexibility and capabilities in the platform, but also really, really focus on business user productivity.

Ram Venkataraman: So when we talk to CIOs, we wanna meet them at where they are in terms of their, I wouldn't say, digital transformation, but their technical skills that they have in the organizations, you know, clients don't wanna become, retailers don't wanna become B2B distributors and manufacturers don't wanna become IT shops to a point where they're building software beyond a certain point.

Ram Venkataraman: So if they're not on that journey, we offer more out of the box, out of what Kibo does and then, we always give them a choice, hey, listen, as you evolve and transform yourself, if you wanna take certain capabilities out of Kibo, you don't have to replatform like the old days.

Ram Venkataraman: You can rip out a piece, you can rip out search from Kibo and put another search platform like Algolia or Constructor.

Ram Venkataraman: If you want to power certain capabilities like our CMS is out of the box and you wanna use full content stack or Amplience or any of those things, you can do that.

Ram Venkataraman: And so it allows clients to have that choice, and that's why we always talk about how composability is important, but decomposability is equally important, right?

Ram Venkataraman: So that's how we kind of help people meet them in that journey that they're on.

Kailin Noivo: That's very interesting.

Kailin Noivo: So how are you thinking about and you coming from the product space, how are you thinking about what you build, what you buy, and what you partner to deliver merchant experiences?

Kailin Noivo: Yeah. Maybe talk to us a bit about, like, how do you think of what's core to the business versus what's ancillary, and then how you, kind of, approach delivering that experience to the merchants themselves?

Ram Venkataraman: Yeah. Fascinating question. Right?

Ram Venkataraman: So when we think about it and most people think about it, hey, Kibo, you're doing so much.

Ram Venkataraman: You're doing ecommerce, you're doing OMS, you're doing subscriptions but when you step back and think about it, every ecommerce player has a catalog of pricing and a promotion engine capabilities built in.

Ram Venkataraman: Every OMS vendor has some notions of catalog pricing and promotion capabilities built in. A subscription vendor has those things.

Ram Venkataraman: So there's a tremendous amount of overlap in these capabilities.

Ram Venkataraman: SaaS companies like us engineer these solutions. Right?

Ram Venkataraman: So what we did is that, hey, listen, we don't wanna think about these as three different solutions.

Ram Venkataraman: We wanna think about it as one set of microservices that we can package and deliver.

Ram Venkataraman: So if it's in these areas of ecommerce, OMS, and subscription, we will innovate and we will build it to the best of our abilities. When it comes to the front end of the stack, as that is changing pretty dramatically and as, you know, user experience, especially as you talked about agentic experiences, those gonna search is gonna be a huge part of it. Right?

Ram Venkataraman: So we don't invest in all of those capabilities.

Ram Venkataraman: Our search is built on core solar, but we leverage all the Gemini models to be able to bring in vector search capability.

Ram Venkataraman: We're not gonna build our own LLM engine there or try to, you know, even leverage some third-party engines in those capabilities.

Ram Venkataraman: Where we don't have core competency in, again, those set of microservices that we talked about, we will go out and partner with somebody to build that.

Ram Venkataraman: So we did that same thing on the dropship side, right? We don't have EDI capabilities, we partnered with a vendor called Orderful.

Ram Venkataraman: We embedded that into our platform, and we're going and leveraging those capabilities.

Ram Venkataraman: So, again, if those microservices are in the ecommerce or MSN subscription space and we have a core skill set, we'll invest in it.

Ram Venkataraman: Otherwise, we'll partner. Building, I think, is a very dangerous thing right now because the buying is a very dangerous thing at this time right now because we don't know the right technologies that are gonna be around or not around.

Ram Venkataraman: And that's why the point I made today, maybe you can build it faster by leveraging AI approaches rather than buying a company, dealing with all the integration issues that come with it, trying to consolidate the tech stack and we have gone through all that, right?

Ram Venkataraman: If you look at our history, we had several companies that we had to resolve and kinda homogenize and get to where we are today.

Ram Venkataraman: And I think buying a company and integrating that is gonna be a lot more challenging in the future than kinda building them rapidly using AI approaches.

Kailin Noivo: Very interesting. You mentioned your AI kinda agent strategy.

Kailin Noivo: You guys are building multiple agents. What are some of the questions that you think your customers should be able to ask and get an answer from these various agents?

Kailin Noivo: Like, what are kind of some of the use cases that you see bubble up to the top?

Ram Venkataraman: Yeah. So think about it. So the first set of agents we are saying to our clients is, hey, we want you to, we want to lower the cost of running Kibo. Right?

Ram Venkataraman: Meaning, you need to be able to configure the platform.

Ram Venkataraman: We talked a little bit about business user productivity.

Ram Venkataraman: So we have lots and lots of admin screens throughout our platform that allows you to configure various types of things in catalog, whether it's a pricing rule, whether it's a promotion rule, whether it's an orchestration rule, whether it's an inventory rule.

Ram Venkataraman: And so the cost of learning that whole platform, it takes them six months to really figure it all out end-to-end if somebody deploys all of these services.

Ram Venkataraman: So the first question, you know, people ask me is like, hey, how can I go faster?

Ram Venkataraman: How can I get time to value? I think that's the question everybody asks. How can we get to time to value quicker?

Ram Venkataraman: Can I deploy the solution in 90 days, in 120 days? And the answer to that is, yes. We can do that, and that's where the agents are really, really helping.

Ram Venkataraman: So, I'll give you an example. You wanna set up a promotion rule, I wanna apply 10% off all these green jackets between this date and this date from this brand of these sizes.

Ram Venkataraman: That is probably to set up a lot of capabilities. It may take you, you know, fifteen, twenty minutes to set that rule up, ensure it's working, so on and so forth but couldn't we say that in English?

Ram Venkataraman: And the system configures it by itself. And that's where we are right now.

Ram Venkataraman: We have the capability right now to actually set that rule up, see that on the screen, say I like it, save it, maybe make a tweak or change it to that rule, and make that rule available very quickly.

Ram Venkataraman: Now fast forward that, let's say, four weeks from now, that rule got applied to an order, and the person seeing that order is not exactly sure why that rule got applied.

Ram Venkataraman: That's where our Explain agents come in and say, hey, and when the user says, hey, why did this rule get applied and this promotion get applied?

Ram Venkataraman: The system will go back to the logs, look at the rule set and come back in an English language to say, this price was so and so because of this, this, and this reason. So those are the types of reasons, and this is across every microservice in the system.

Ram Venkataraman: There will be configured rules, Configured agents, and there will be Explain agents, right? And so those are agents that are running in the platform.

Ram Venkataraman: The other thing we talked about is what we call Engage, that's basically conversational in the front end of the brand side of the B2B and distributor-manufacturer side where, you know, their shoppers and buyers are engaging that brand through agents that basically can allow them to purchase a product or self-service with them post-purchase.

Kailin Noivo: And the sales agent not to rename it, but this the agent that's customer-facing—

Ram Venkataraman: We call it Engage. We call it Engage.

Kailin Noivo: Yeah. So it's like someone, it's almost like a salesperson to a degree.

Kailin Noivo: That's really interesting.

Kailin Noivo: And you're giving the out-of-the-box capability to your customers to actually deliver that?

Ram Venkataraman: You're giving that out of the box. And not only that, we also work with, one of the things that we wanted to solve is how do we make this work in a composable world, right?

Ram Venkataraman: Not everybody wants, people may want this Engage agent or the sales agent you talked about, but may not have all of Kibo's services running there.

Ram Venkataraman: So can I make it work with Salesforce's Commerce Cloud?

Ram Venkataraman: Can I make this work with Sterling's back-end system in terms of leveraging the OMS capabilities with maybe our competition out there, but deliver great value for our clients?

Ram Venkataraman: So that's a big approach in terms of our architecture is that certain agents only work with Kibo’s capabilities and services. Some agents can work across and with other platforms’ services too.

Ram Venkataraman: So as MCP kicks in and more and more platforms offer MCP, obviously, their orchestration is gonna get easier, but we're not there yet.

Ram Venkataraman: And there are some lots of legacy systems that will never get MCP capabilities.

Ram Venkataraman: So how do you make that work? And so we've figured out ways to train agents based on API calls to be able to orchestrate those experiences on the brand's website through conversation.

Kailin Noivo: Talk to me a bit about, how are you seeing from an adoption standpoint?

Kailin Noivo: Like, are you seeing internal agents, like Config and Explain, get more adoption and customer facing than agents?

Kailin Noivo: Maybe curious about the adoption.

Ram Venkataraman: Yeah. The adoption is more on the Engage side yet. Right?

Ram Venkataraman: It's because they wanna improve, again, there's a lot of pressure in the market, you know, competition is doing it.

Ram Venkataraman: We're going through it almost feels like the first few years of the Web 1.0 age when, you know, getting a brand site up and I'm old enough to know those days in the early 90s and, sorry, late 90s and early 2000s where people are trying to get this up and running.

Ram Venkataraman: We're going to the same thing where everybody wants a conversational agent.

Ram Venkataraman: So we're seeing a little more demand in that area versus, hey, I wanna leverage Configure, and Explain but I think all that is coming.

Ram Venkataraman: As it's coming, as more and more people start leveraging these capabilities.

Ram Venkataraman: People are focused on how do I increase a top line and that's really a positive thing when you can have a conversation on a website with an agent, and it's amazing to see these experiences and what these LLMs can generate in terms of capabilities to upsell, to cross sell, all the things that we're used to through recommendation engines and things like that in the past.

Ram Venkataraman: But those experiences are so much more natural through a conversation versus having to do that, you know, click 10 links and then find the right product.

Kailin Noivo: Are you concerned about GBT transactions?

Kailin Noivo: Like, basically, people are gonna be in an LLM, whether it's Google Gemini, ChatGPT, or Claude, and they're actually just gonna complete a transaction from A to B through there and cutting out part of the platform effectively.

Kailin Noivo: How do you feel about that?

Ram Venkataraman: I don't feel that that is gonna cut the platform out because I think, you know, if this has happened, Google would have figured it out.

Ram Venkataraman: We've been all giving catalogs to Google for 15 years.

Ram Venkataraman: Most of our clients give a Google feed, a catalog feed, a pricing feed, an inventory feed to Google.

Ram Venkataraman: Google has tried Google Shopping for many, many, many, many, many years, and it's never worked and, you know, there's two or three challenges, I think, in my point of view.

Ram Venkataraman: I think, you know, using a baseball analogy, we're probably the bottom of the first right now. It's still too early to really worry about that.

Ram Venkataraman: Largely, I would say that all of these retailers have very complex pricing mechanisms and promotion mechanisms.

Ram Venkataraman: Unless OpenAI is willing to build a full commerce platform, they're gonna have to come back through an MCP server into the commerce platform to be able to leverage all of those capabilities.

Ram Venkataraman: So I can think of this as another headless client that sits on top of commerce platform's APIs and MCP servers, and I think that's definitely gonna happen.

Ram Venkataraman: But I don't know whether they can cut out the commerce platforms fully because there is so much complexity in all of these things that, you know, each of these businesses have a unique differentiation.

Ram Venkataraman: And the differentiation is in these business rules that they have that are exposed as APIs.

Ram Venkataraman: And I think they're gonna have to come back to the commerce services, especially on the back-end side of things.

Ram Venkataraman: Now search, I think that probably is gonna get really commoditized because these agents would be able to do that but then, until OpenAI and Claude and Gemini will probably the easiest can figure out a way to put ads, you know, if I am Ace Hardware and I'm Home Depot, let's take the same example, how is that grill that Ace sells gonna show up higher than the one that

Ram Venkataraman: Home Depot sells? Right?

Ram Venkataraman: And there's gonna have to be some market where they bid on it.

Ram Venkataraman: So, you know, my hypothesis is OpenAI is gonna have to build an ad-based platform, and it's gonna become, in some shape or form, a story that looks similar to Google over a period of time.

Ram Venkataraman: I mean, Google makes, I don't know, $270 billion the last time I looked at it in the ads business. I don't know how many people it's gonna take to buy $20 a month to get to that revenue.

Ram Venkataraman: They're gonna have to pump into ads or this is not gonna be a business model over a period of time.

Ram Venkataraman: That's one more point. One more point is, I think from a brand perspective, they're gonna pay OpenAI a piece of the transaction, they're gonna pay the payment provider a piece of the transaction, and they're gonna pay the commerce platform a piece of the transaction.

Ram Venkataraman: So at some point, the shoppers are gonna be smart enough to say, hey, if I go to the brand's website, I don't have to pay OpenAI or anything.

Ram Venkataraman: So there's gonna be some interesting commercial things to figure out here and how they monetize it.

Kailin Noivo: I agree. And I think this is very similar to, like, the Amazon situation. Amazon is 37-ish percent of retail sales, like, I look at this as kind of the marketplace theory. Right?

Kailin Noivo: Yeah. There's probably a cap on marketplace, if that makes sense, and it's not gonna be a 100%.

Kailin Noivo: I think, actually, Amazon potentially is at risk in this context because it's kind of the value of Amazon through a tool, and that could potentially inch it up to 50% of global sales.

Kailin Noivo: Who knows?

Kailin Noivo: But to your point, it's probably never gonna be 100%. Well, this has been phenomenal, Ram. I really appreciate you hopping on the show. This was super awesome. I hope you don't mind that we went too long on AI, but I think that -

Ram Venkataraman: That's okay. I really enjoyed talking about it. Yeah.

Kailin Noivo: If we'd chat about anything else, I don't know if we'd be doing the right thing. So I appreciate you taking the time, and thanks again.

Ram Venkataraman: Thank you so much. I appreciate it.

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