This week, we are joined by Atena Reyhani, Chief Product Officer at ContractPodAi, for an engaging discussion on the intersection of AI innovation and the legal industry. Atena brings her deep expertise in AI-driven product development and shares insights into the trends shaping legal technology and how ContractPodAI is at the forefront of this transformation.
The conversation kicks off with a focus on the prevalence of conversational user interfaces (CUIs) in modern legal tech tools. Atena explains that CUIs, inspired by platforms like ChatGPT, are intuitive and reduce the cognitive load for users, making adoption easier. “Conversational user experience is now one of the ways of interacting with super intelligence,” she notes, highlighting how this design helps bridge the gap between human communication and AI capabilities. Atena also predicts a future shift towards deeper human-AI collaboration, moving beyond simple interactions to robust tools that integrate seamlessly with user workflows.
When asked about the challenge of brand differentiation in a landscape where many tools appear similar, Atena emphasizes the importance of moving from basic chatbots to comprehensive, end-to-end solutions. She points to the rise of agentic AI, where multiple AI agents work together to provide dynamic, actionable insights. According to Atena, “AI can now analyze information, outsource tasks, and dynamically engage multiple AI agents to perform end-to-end operations,” paving the way for truly intelligent legal platforms.
Atena delves into how ContractPodAi leverages AI to address real-world challenges in legal operations. With its Lea AI solution, the company has expanded beyond contract lifecycle management (CLM) to broader enterprise applications such as compliance and obligation management. Atena reveals an exciting new initiative, the Lea Marketplace, which she describes as “a one-stop shop for enterprise legal GenAI,” likening it to the Salesforce or Microsoft Marketplace. This platform will enable partners and subject matter experts to accelerate innovation through collaborative, industry-specific solutions.
Reflecting on her career in AI and her recognition as an award-winning innovator, Atena speaks passionately about the tangible impact of AI on businesses and individuals. She also underscores the importance of diversity in technology development, stating, “Women bring a diverse perspective that is crucial for innovation.” Atena encourages more women to step into leadership roles and shape the future of AI and legal tech.
The episode concludes with Atena’s predictions for the legal tech industry. She identifies key challenges, including aligning AI capabilities with organizational needs and ensuring effective user adoption. “It’s one thing to have the technology and another to use it to its full potential,” she observes, stressing the importance of strategic deployment, training, and change management. Atena’s optimistic vision underscores the vast opportunities for AI to revolutionize legal operations.
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Blue Sky: @glambertpod @marlgeb
Email: geekinreviewpodcast@gmail.com
Music: Jerry David DeCicca
Transcript
Marlene Gebauer (00:07)
Welcome to The Geek and Review, the podcast focused on innovative and creative ideas in the legal industry. I’m Marlene Gabauer.
Greg Lambert (00:14)
and I’m Greg Lambert.
Marlene Gebauer (00:16)
So on this episode, we’re joined by Atena Reyhani, Chief Product Officer at ContractPodAI. Atena, welcome to the Geek in Review.
Atena Reyhani (00:23)
to be here. Thank you for having me.
Greg Lambert (00:26)
All right, but I thought before we jumped in and talked about your work there at ContractPodAi, we’ve had, Marlene and I have had this discussion going on for a number of weeks now and we thought we would bring an expert on to discuss it with us. And that is looking at, yeah, a real professional. And that’s looking at the user interface or the user experience of most of the new legal tech AI tools that
Marlene Gebauer (00:41)
We need a professional.
Greg Lambert (00:54)
that have come out over the past year or two that look very similar to the interface that ChatGPT has. So, Atena, I wanted to bring you in on this and from most of the products that I’m seeing in the market, they’re coming out with this three panel user interface that looks a lot like the ChatGPT interface.
And since you have a good background in user experience as well, I wanted to get your thoughts on why do you think that we’re seeing this type of similar interface out there? Or maybe it’s just me, maybe, am I wrong? it?
Atena Reyhani (01:34)
Yeah. No, it is. No,
that’s very common actually. Well, conversational user experience is now one of the ways of interacting with super intelligence, isn’t it? If we really think about it…
us as human, of course, have this natural inclination of conversational communication, It’s either in voice or writing. So it really makes sense for a lot of these products to start there and use that as a starting point to bring a chat pod and the platform that are already there or the systems of records that elsewhere to really start to provide.
this type of technology and capabilities to the end user. It has a lot of advantages, right? It’s intuitive, it helps with the barriers of adoption. easy, it helps with the barriers of adoption, right? It reduces that cognitive load for users to really go learn a new user interface to use the technology. So it’s a great starting point.
Marlene Gebauer (02:32)
easy.
Atena Reyhani (02:49)
And that’s why you see a lot of it being common. They actually in the products world, they call it CUI, conversational user interface. It’s very common. Yeah.
Marlene Gebauer (03:00)
So I have a follow up question on that. mean, from a
usability standpoint, makes perfect sense. What about like from a branding standpoint though? I mean, if they’re all looking the same, how do they distinguish their brand?
Atena Reyhani (03:13)
Yeah, that’s a great question. I think one of the areas to think about is that, you know, that chat box or conversational user interface is just the beginning. It’s just the starting point, right? The AI is really advancing and especially with the recent technology of agentic AI, we are now seeing a lot of more comprehensive solutions that are really tackling real end-to-end problems. So rather than
having a chatbot and the AI just waiting for a user to come in and ask a question to respond. Now we are seeing these end-to-end solutions that need really different type of user experience and user interfaces that accommodate this end-to-end solution. And when it comes to branding, when it comes to core competencies of products, it really remains the same.
It’s like new tools, new ways of communicating, starting with the chatbot, but growing to a more end-to-end comprehensive type of products that all the solutions are going to offer.
Greg Lambert (04:26)
Yeah, do you think one, do you think the user interface will change over time or do you think that it’s going to get away from the chat bot and more into like the product, more into Microsoft Word, more into Outlook or wherever the attorneys are working?
Atena Reyhani (04:47)
Absolutely, it is definitely going to be where the user is for maximizing that adoption. I really think that we are going to shift from these simple human AI conversation to more deeper human AI collaboration. And there are going to be a lot of tools that are going to be needing to really get to that and graduate to that. Think of it as talking with AI.
and going to actually having tools and user interfaces to work with the AI.
So actually, I think this is great topic. Let’s break it down, thinking about solutions that are very complex, like traditional platforms like CLMs, CRMs, ERMs, all of the solutions that are out there. These are the type of solutions that the user interface has a lot of, if you think about it, predefined workflows, like their navigations, their forms, their dashboards.
So the users really need to understand where to go take action, so on and so forth. And these systems are really designed to accommodate how software works, not necessarily how human communicates and human works, Now we’re talking about AI for solutions that the dependencies on databases and the traditions
of tech stacks are really starting to fade, right? So now AI can really analyze the information, outsource and dynamically drive intelligence from it, engage multiple AI agents in the background to really perform a task end-to-end. That really impacts the user interface that is needed to accommodate this kind of human AI collaboration.
Greg Lambert (06:49)
Yeah, yeah. I’m still waiting. Do you remember the, I don’t know if you saw it earlier, about June or July of last year, Thomson Reuters came out with this kind of flashy, like a two minute video of like an associate was out at happy hour and a project came in and she was able to like forward the information right from her phone to the AI to have the work ready.
or when they got back to the office and all that. So I imagine it’s one of the things that we don’t see a lot of and that is kind of both the mobile and remote style tech or secondary tech to kind of queue in the AI agent to get started and then have that information back at you. So I can see where in the near future if it’s not already happening with some products that there’s the integration of you can.
start it here and then, you know, work on it or finish it somewhere else.
Atena Reyhani (07:50)
Yeah, absolutely. It’s going to be ecosystem of agents each having very targeted expertise that are going to work together. So actually, know, action and tasks. Like in that example, you know, you could ask the first agent to start a process, but that agent is going to likely decide that it needs more tools, it needs more agents and, you know, other actions to be done. it’s really, you know, thinking about
is going from solutions that are predefined and it’s like this siloed layer technology to platforms that are empowered by multiple AI agents. I think of it as going from a printed map to self-driving cars that have dynamic GPS. It’s really just bringing all aspects to work together and it’s very exciting.
Marlene Gebauer (08:44)
Well, this, I mean, this is interesting because, know, if, what, if I’m understanding this, you’re saying, cause we have an agent and then the agents will decide on other agents and, sort of where, where does the human in the loop come in? If, if they are kind of making those determinations in terms of the, best, additional tools to use.
Atena Reyhani (09:05)
Yeah, I think the human is in the loop is going to be as part of that human AI collaboration, right? There are recommendations that are coming in and there’s the human that makes the decision on what direction to go and asking what needs to be done. And then there are a series of agents and series of AI models that are going to be engaged to provide that to the human. Let’s take like the legal
work, for example. Just imagine instead of having forms to fill out and going through the standard process of negotiation, going through standard process of approval, so on and so forth, actually having AI agents that are targeted that they can analyze the information within the unstructured data set that we have in legal, organizational, like a lot of different
and
data sources and really dynamically not only identify the information but understand and analyze the information and take actions on top of it. And then when it’s needed, bring in the human for approval, bring a human for different actions that are needed but automate what is possible.
Marlene Gebauer (10:26)
This is interesting because basically the human is saying, is what I want to do, or this is what I want to accomplish. And then the agent will decide what tool to use to do that. And I’m assuming this is sort of a closed environment of tools like at a firm. There’s only so many things you can use. And I think it’s interesting because when we’ve had, Greg and I have had this conversation, and this conversation has gone on in the industry for years, that oftentimes users don’t know all the things that they have.
Greg Lambert (10:55)
that’s so true.
Marlene Gebauer (10:56)
And it’s always a challenge to try and get them to promote that type of awareness. And I think with Gen.ai, we’ve actually had a renaissance of being able to do that because people say, well, can Gen.ai do this? It’s like, well, no, we have this other tool that does it. But this is kind of one step further where they’re not going to have to even know the tools at all because they’ll just say, this is what I want.
Atena Reyhani (11:13)
Yeah.
Exactly.
Marlene Gebauer (11:24)
That’s
brilliant. I can’t wait.
So, Atena let’s talk about ContractPodAi. Would you mind telling us what ContractPodAi does? And, you know, if I were in the legal industry, what problem would I be facing that would make me reach out to ContractPodAi as the potential solution? I said ContractPodAi three times in that sentence. That was pretty good.
Atena Reyhani (11:46)
Yeah.
Well, we are an enterprise legal AI solution. And what that means is that we have an ecosystem of expert legal models in the comprehensive solution around it. That is, you know, the frameworks, the guard rails, the infrastructure innovation, everything that enterprise or organization need and can use to really operationalize AI at a scale. Now we started our journey over
a decade ago in contract lifecycle management space. And from the beginning, our emphasis was AI and applications of intelligence. specifically in the past couple of years, we strategically increased our investment in our GenAI solution called Leah.
So Leah makes us a leader in Gen.AI for CLM, but also helps us bring in the intelligence to broader enterprise ecosystem and broader enterprise work streams, like use cases like compliance, obligation management, entity analysis, and many other adjacent use cases that we offer products for. So for organizations that are dealing with the complexities
of contract negotiations, dealing with the complexity of contract management, ensuring compliance, analyzing obligations, so on and so forth. Our solution delivers that intelligence that they need to really automate and then simplify and scale these processes very efficiently.
Marlene Gebauer (13:35)
Now know it can be used both for sort of client work as well as internal work. Do you have a sense of where it’s being used most?
Atena Reyhani (13:46)
It is a combination of both. We have lot of enterprise organizations that are using our products in legal procurement, sales processes. We also have our partners like PwC and KPMG that are using our product for their legal services in addition to offering our products to their enterprise organizations. it’s kind of a combination of the both, specifically, especially actually.
with our Leah Gen AI solution. It’s really broadened our reach, it broadened our market to both sides of the house.
Greg Lambert (14:29)
Now, you talked about how ContractPOD AI has established itself as a CLM tool and then with the introduction of Leah, you know, it combines that CLM with the document management system capability. So what challenges or market needs inspired this hybrid solution and, you know, how do you see it reshaping like legal operations?
Atena Reyhani (14:59)
Yeah, great question. Well, it’s all about tackling the real problems that enterprise organizations are facing, right? If we think about it, contracts are really critical and essential business assets for organizations. But in reality, they don’t live in isolation, right? They are part of…
broader connected ecosystem. Take commercial construct of a contract.
or in SLA terms. These all exist within the contract after the deal is completed. Still, a lot of information that is related to the performance of these terms are in adjacent systems, right? And often, they are in unstructured format, in documents, they’re not properly processed, that it really makes it difficult to
access and not only that, it makes it really difficult to act on efficiently. So we really identified this opportunity to create connected intelligence with these agents that are capable of identifying this information at the source, driving intelligence from it, eliminating the need for manual entry of data.
and having proactive actions. And we really think that this is going to drive smarter and more connected operation for our customers.
It also, if you think about it, really aligns and kind of signals the broader shift that is happening in the SaaS market in general, as we are going from more of these kind of siloed layered technologies to these platforms that are now empowered by agentic AI and each having expert AI that can work together to offer this end-to-end task.
Greg Lambert (17:12)
Yeah, I’m curious when you were promoting this as a DMS, because I’ve talked with a lot of DMS companies and they’ve been, even though they’re doing things with artificial intelligence, they’re really kind of skittish on some of the things with the security issues around, the law firms, you know, buy their product for the security.
and obligations, regulatory, ethical obligations that they have to do with the documents that they manage. Is that something that, are you talking about a DMS just for like the contracts or are you talking like a full DMS?
Atena Reyhani (18:01)
It is so that the Leah drive and you know, kind of Leah, you know, in general, our solution is that, you know, command center not only for contracts, but adjacent information that drives decision and intelligence on top of the contracts. We’re talking regulatory requirement, company policies, procedures, companies, strategic compliance, you know, standards and so on and so forth. So many adjacent
you know, information that goes on top of the information within the contract to drive those kind of actionable intelligence. So it’s a holistic connected intelligence is that we think of it as a command center for a gen AI intelligence. Now, great point on privacy and security. that is really even like on contract life cycle management or like any product that enterprise organizations use, privacy is so important. Security is so important, right? And that,
Those are such a foundational considerations for us as a provider to have the infrastructure, the AI models, the innovations that we need to guarantee the security, guarantee the privacy and the performance for our customers.
Marlene Gebauer (19:21)
I’m curious if there are any, I don’t know, surprising adjacent areas where you could pull information for the contract.
Atena Reyhani (19:32)
Well, I’m not saying it’s necessarily surprising.
Marlene Gebauer (19:35)
Something people wouldn’t necessarily, something people wouldn’t necessarily, it’s like, it’s not surprising to you, but something that
people wouldn’t necessarily expect, where you could mine that.
Atena Reyhani (19:43)
Yeah, there are a couple of
Yeah, no, absolutely. Well, mean, there are so many use cases in different area, industry specific use cases, subject matter expertise that now the problem statement was on the table for a long time, but the technology to really accomplish that was not there. Now with the capabilities of AI, with the capabilities of technology, we are looking at solving those kind of problems.
For we’re looking for investment firms. One of the largest investment firms are now using Leah for their entity analysis and SEC reporting. So these are the type of analysis that there are on interconnected documents. Contracts is one part of that, but there are interconnected documents that are ever evolving.
analysis
that needs to be done is not necessarily on the information that explicitly mentioned on the document. So there are certain information that needs to be understood by AI and then there are process seasons and things, algorithms that need to be applied for conclusions to be made to drive classification of the entity. Is the entity at that point an affiliate or financial instrument? is, you know, like what are our set of answers
for every single entity, every single quarter that we need to do this kind of processes. These were type of, it’s just an example, it’s one of the use cases that the work was there, it was being done semi-manually, course, extraction tools were there, but these kind of analysis were on the table, the problem was on the table, but technology was not there for us to be able to attempt them.
So now they are, if they’re very, very complex use cases, but very valuable, very impactful type of use cases we’re working on. Yeah, yeah.
Marlene Gebauer (21:54)
The tools are catching up with the need, so it’s good.
Now, you have had a significant career in product innovation, particularly in AI-driven solutions. the world would be your oyster on that, right? So what led you to focus on the legal technology industry? And how does your background in AI and digital transformation inform your work at ContractPodAi?
Atena Reyhani (22:20)
Thank you, Marlene first. Well, legal and enterprise space is really exciting because of so much opportunity that there is here for innovation. The opportunity and then at the same time the challenge is really transforming mountains of legal, operational, organizational data to actionable intelligence that really create value.
value
for organizations, right? And with my background, I have worked with many generations of AI and have partnered with customers in various industries for deployment and adoption of the tools. Now, one of the common themes for success that I see is adding this perspective of value in addition to what are the technology
and what it is and how to use it to the value that it brings to the table and the impact that it makes for our organization. this is going to be even more important when it comes to the power of Gen.ai and agentic.ai. And at Contract Pod.ai, this really drives everything we do. We’re not just providing solutions to problems as it comes our way. We are really looking at how we can
and
redefine the way that legal teams work and the enterprise work stream this process, right? With the intelligent tools that really streamline the operation, like really bring in those tools that enhance decision making and entirely look at new ways of doing things. And this is extremely exciting. opportunity is massive.
Greg Lambert (24:14)
That was a very polite way of saying that the industry still has a ways to go. Opportunities are great. You had talked about kind of telling the story of the value that’s created with it. Are you finding that the legal industry, at least the people that you’re interacting with, are responding to that?
Marlene Gebauer (24:18)
We need help.
Atena Reyhani (24:22)
That means opportunity, that means a lot of opportunity for product creative.
Greg Lambert (24:43)
that type of storytelling about the value of the solution.
Atena Reyhani (24:49)
No, it’s very interesting, Greg, because before what I call AI moment, two or three years ago when we started talking about Gen.AI, everyone looked at AI. I mentioned at ContractPodAi, we have been offering AI-based technology to the market. And it’s very interesting because before the AI moment, our focus in a lot of our conversations with our customer was not the technology, was the value.
And then all of a sudden, of course, there is a huge momentum in the market. Everyone has AI initiatives and we’re looking at how to use the tools. And for a little while, for a year, a year and a half, that was the trend. All we’re talking about is technology, technology, technology. And then now with the maturity of the market, a lot of those questions, a lot of those are really just kind of settling down. Interestingly, we’re going back.
back
to the value conversation. Not only what is the technology, but what can we do with the technology? How can we incorporate it? How can we operationalize it at a scale? Work on user adoption. Really scale it at a larger scale. Operationalize it at a larger scale for organizations to really realize value from the technology that they bring to.
to their organizations.
Greg Lambert (26:21)
Yeah, yeah, good. I’m glad we’re worn out the topic of the Gartner hype cycle. But it feels like we’re at that point now where people are looking for results, not just give me technology because I need technology to tell my clients I’m using technology. And now it’s more here’s what I’m bringing to this for the value part of it. So that’s good.
Atena Reyhani (26:37)
Yeah.
Yes.
Marlene Gebauer (26:48)
Yeah.
Greg Lambert (26:50)
I know there’s, and you’ve mentioned that you guys have dealt with AI for many years now, not just generative AI over the past couple of years. So as things progress, how do you see this affecting the future roadmap of ContractPodAi Are there things that you’re looking to develop and bring out in the near future that you’re, or maybe even the far future that you’re excited to?
about.
Atena Reyhani (27:21)
Yeah, well, we definitely have our finger on the pulse and closely closely monitoring the market by partnering with our customers, partners, both on legal and technology side and experts in the market. And definitely that is influencing our roadmap. One of the areas that is emerging more and more
is this transition from general models to really vertical intelligence, like expert and targeted solutions, expert and targeted models that can work together as we talked earlier to really empower a platform.
And based on that, one of the initiatives that I’m very excited about that we are working on at ContractPodAi is called the Leah Marketplace. Think of Leah Marketplace as Salesforce or Microsoft Marketplace or an app store, one stop shop for everything in enterprise legal gen AI.
And if you think about it today in creating a lot of our features and functionalities and formulating our product, we really partner with our customers. We partner with our partners like PwC and KPMG and other experts in the market to bring their expertise in formulating their product. And with this initiative with Leah Marketplace, what we are really looking at is systematically operationalized.
and get within the solution, within the product. And I’m personally very excited about it because I think this initiative is really going to expedite the speed of innovation in the market, right? Because there are going to be these expertise that are coming in from experts in the market, our partners that are going to be very industry specific, or they have subject matter expertise
Marlene Gebauer (29:12)
you
Atena Reyhani (29:24)
on some areas in the domain that, know, you know, Leah Marketplace is going to help expedite the speed of these kind of innovation. I think of it as crowdsourcing innovation, starting with leaders in the industry. I’m really excited about it.
Marlene Gebauer (29:41)
Very cool. So, Atena, you’ve been recognized with two prestigious Globee Awards, most innovative women of the year and women excellence, women excellence of the year in product development for your innovative work in AI. we talked about why legal technology, but let’s, let’s be more general. Like what drives your passion for developing AI products in general? And also
You know, what value do you think women bring to developing legal tech and specifically AI products? Because it is a very male dominated space, right?
Atena Reyhani (30:20)
Yeah, well for me, the drive comes from really seeing the tangible impact of AI on businesses, on people’s life and work, and that is very rewarding. from early on in my career in AI, it was very clear that the technology has an incredible potential. I started working with use cases like brain-computer interfaces, computer vision.
classification,
extraction, anomaly detection analysis, so on and so forth, all the way to now generate of an agentic AI and the opportunities are massive.
And it’s incredibly fulfilling to create tools that make these complex tasks simpler and really offer the tools for better and more advanced ways of doing things. It’s really rewarding. It’s my drive to really provide these tools.
As for women in AI, I really believe that we bring in that diverse perspective that is so crucial for innovation.
It’s, I personally know so many very impressive women that with different backgrounds, with different areas of expertise, not necessarily AI, not necessarily even legal, right? Like there is very, it’s the power of the community with so many different perspective and background that these women are stepping in, taking the lead and participating in shaping our future with this impressive technology. And I encourage more of us to take active role.
Greg Lambert (32:16)
Congratulations on the awards. are fantastic. Very impressive. So, Atena, we’re at the point now where we ask all of our guests our crystal ball question. So I’ll ask you to pull out your crystal ball and peer into the future for us.
Marlene Gebauer (32:20)
this.
Atena Reyhani (32:21)
Thank you.
Greg Lambert (32:33)
and answer what changes or challenges do you see facing the market or even ContractPodAi specifically over the next couple of years that you think we’ll need to address.
Atena Reyhani (32:49)
I think we often talk a lot about the technology and the potential of the technology. Now, the reality is that it’s one thing to have the technology and another to use it to its full potential to create value. Right? Yeah.
Marlene Gebauer (33:05)
It’s like your iPhone that you use like 5 % of it. You know, it’s like, it’s great, but you only use half of it.
Greg Lambert (33:09)
Or your brain.
Marlene Gebauer (33:10)
Yeah.
Atena Reyhani (33:11)
Yeah,
yeah. And I think that is going to be one of our challenges in the industry. And that is, number one, really aligning these capabilities of AI to practical organizations needs and being able to operationalize it at the scale to translate technology to value. And that means a lot of like strategic deployment of the products.
stretch a strategic deployment of the technology. Really a lot of user training that is going to help with user adoption and that change management across enterprise work stream. I think these are amongst the challenges that as an industry we are going to be facing in coming months and years that is going to grab our attention and focus.
Greg Lambert (34:05)
you hit all the hard parts, strategy, deployment, training, change management, all the things that the legal industry is known for doing well.
Marlene Gebauer (34:09)
change management.
Atena Reyhani (34:15)
Yeah, but it’s
Marlene Gebauer (34:15)
You
Atena Reyhani (34:16)
very similar to what we did with other technology transformations. it is AI, it’s new technology, it’s new ways of doing things. But a lot of those expertise that we gathered in going through digitalization and other transformation for adopting other technologies, a lot of those learning still apply to AI and GenAI products.
Greg Lambert (34:42)
Atena, thank you very much for taking the time to talk with us today.
Atena Reyhani (34:48)
course, thank you for having me on the show.
Marlene Gebauer (34:51)
And of course, thanks to all of you, our listeners, for taking the time to listen to the Geek in Review podcast. If you enjoyed the show, share it with a colleague. We’d love to hear from you, so reach out to us on LinkedIn.
Greg Lambert (35:03)
Atena, I’ll make sure that we put links on the show notes. But if the listeners and viewers want to learn more or to reach out, what’s the best place for them to go?
Atena Reyhani (35:15)
I think the best way would be connect on LinkedIn or check out the ContractPodAi website.
Marlene Gebauer (35:23)
And
as always, the music you hear is from Jerry David DeCicca Thank you, Jerry.
Greg Lambert (35:28)
Thanks, Jerry. All right. Talk to you later, Marlene.
Marlene Gebauer (35:30)
Okay, bye bye.
Atena Reyhani (35:31)
Thank you.