Your AI Meeting Agents Aren’t Enough: Otter.ai's Sam Liang on Enterprise Knowledge

(upbeat music) Hello everyone and welcome humans to the Neuron podcast. I'm Corey Knowles, editor of the Neuron and we're joined as always by Grant Harvey, writer of the Neuron Daily AI newsletter. How's it going Grant? - Going well, going well. Today we've got Sam Liang, the co-founder and CEO of Otter AI, before Otter, Sam built the Blue Dot for Google Maps. You know, that thing that tells you where you are. Now he's transcribed over a billion meetings and last I heard crossed a hundred million in annual revenue, which is pretty awesome with less than 200 people at the time. That's pretty awesome. Welcome to the show, Sam. - Thank you, thank you for having me here. - Yeah, so you recently announced that Otter is moving beyond being just a meeting, no taker app and building into an enterprise knowledge base with agentic workflows, MCPs in there, kind of trying to take the insights that people get from meetings and then expand that and connect all of your enterprise tools to it. That is a big, awesome strategic shift. Could you explain the kind of the thought process there and what all you're doing in the enterprise space? I think it's really awesome. - Yeah, of course. I wouldn't use the worst shift. I would say it's a evolution. We created the AI meeting notaker space, basically we started back in 2016. We launched our first product in 2018. Then we built the Otter AI meeting, no taker that can join your Zoom meeting, Google Meet, Microsoft Teams, Web Apps. No matter what you use, Otter can help you. Can work for online meetings, for offline meetings, like if we meet in person as Starbucks or restaurant, we can use Otter mobile as well. We also recently released the Otter Mac book or working on a Windows version as well. So I would say there are two stages. The stage one is the meeting, no taker. The idea is that all of us spend so much time in meetings under a lot of data show that enterprise knowledge workers spend at least 30% their time in meetings. And if you're a manager, if you're VP, you spend maybe 50, 70, 80% of your time in meetings, traditionally all of this data is lost. People use paper notebook, I still have paper notebook in front of me or Google Doc or notion to manually take note. So we create the AI meeting, no taker to automate all of that. Then we see that the more and more people are using this, even in Fortune 500 companies or tons of people using the author. But most people are still using it as an individual tool. They record something, they keep it to themselves. But the value is way bigger if you aggregate all this meeting notes as a team. For our cell, for example, we have just over 200 people now. We record almost all our meetings in the last eight years. Sales meetings, with customers, marketing meetings, product, project management design, recruiting, both external meetings and internal meetings. That allows us to operate really efficiently. We organize the meetings in either public channels where private channels are very similar to the way people organize their workspace on Slack. We actually build other workspace using the same model as Slack because we see the similarity between Slack and other. Because basically Slack, you communicate it using text messages. But on other, we capture all the meeting contents where you communicate using voice. The similarity is really strong because between Slack and other, you basically talk to the same group of people on the same set of topics. So that's why we build other workspace in a very similar way to Slack. So other workspace allows you to organize and manage all your meeting contents. So effectively, it creates a meeting centric knowledge base. The reason I use a meeting centric, the reason is interesting is that traditionally, when people think about knowledge base, they only think about the written documents, like documents in the Google Doc, notion, emails, for Slack message, or some data in my SQL CRM. People really think about the voice data because traditionally, all the voice data is all lost. But now with order, we help people capture that voice and meeting data. And we create this workspace to help you organize it so that you can find the content in the right relevant channels, or you can search globally. In our company, you can almost find anything in any team. Oh wow. No matter where you work. So most of the content is accurate public. The idea is that to reduce information silos. You know, when-- again, in the past, almost no meeting is captured. But now some meetings are captured. But most people still keep it to themselves, keep the meeting nodes to themselves. So that each team-- there's still a wall between each team. It really slows down information dissemination, work propagation. That's slow down the operation of your team, the crude amount of inefficiency. Yeah. So we see this is why it's important to create a meeting-centric knowledge base. Another reason is that if you think about it, the number one in for most enterprises actually meetings is the most expensive activity. Most people didn't realize that. Just think about how much time or the team members spend in meetings. Yeah. Again, the set. It is a lot. If you're a manager, if you're VP, you spend more than 50% or 70% of your time in the meeting. Is that effectively the employer spend most of their money paying people to go to meetings? Yeah. You can count up all of the salaries of the people involved, and you can say how expensive the meeting is. Exactly. If you spend 50% your time in meetings, effectively half of your salary spend in meetings. Traditionally, there's not even a method to evaluate. Are these meetings even effective? Is it? Right? Yeah. What's the return on that investment? What are the contents that people talk about? Again, people can just-- brain can remember a small fraction of the contents of the meeting. And they forget really fast within the week. 90% of the things they're ready for God. So you know, the facts are pretty clear right now. AIOT is really reshaping industrial efficiency, security, and decision-making in a very real way. We've all heard the buzz around artificial intelligence of things. But what's interesting is that it's finally moved from promise to performance. Companies are actually seeing measurable improvements now in efficiency and resilience and safety, even in decision speed. And the organizations that are leaning in the hardest, they're pulling ahead already. A new global study from SaaS digs into this shift, looking at how leading manufacturers and energy organizations are combining AI and IOT to run smarter operations, accelerate their company innovation, and build a genuine competitive edge. And if you're wondering whether now is the time to act, the takeaway is pretty direct. It really is right now. So if you want to understand what the top performers are doing and how you can accelerate value from AIOT in your own organization, go check out the full findings from SaaS and their new study. It's packed with insights you can actually put to work right now. Learn more and find out how to accelerate your AIOT value today with SaaS. We've got a full link in the description ready to go for you. Another issue is like, for instance, say you're having a meeting and you're using the built-in Google transcription. And then it-- you know, that's nice that it's transcribing everything for you. But it's sitting in a Google doc. And unless you go back and check that Google doc, that data is just still as lost as if you had had the meeting and nobody transcribed it. It's there, but nobody's doing anything with it. Yeah. That happens to me a lot. Or will transcribe a meeting and it's just-- Yeah. Unless you share the meeting notes with the team, with even cross-functionally, the value of that node is very limited. So it's really important to create that network effect of meeting data. The definition of natural effect is that the more content is created, more people have access it, the-- higher value it generate. So this is, you know, again, why a meet and send trick knowledge base so important. Another point I want to make is that I already saw some data that claims, I don't know how true it is, that claims that 50% of the written document on the internet, new content is already generated by AI. Rather than written by human manually. If you think about it, it may be in a few years, 90, 95% of the written document will be generated by AI. So people will rarely write themself. - I can see writing being a lost art. - Yeah, especially as voice transcription is better. - Unless you are a writer by design, I think that is probably the case. Most people are not writers by design. Most people hate writing. - Yes. - However, everyone talks. Everyone talks. And no matter how advanced AI is, people won't stop talking. - That's right. - That's true, no one's gonna make you stop talking. - Yeah, we're talking on this podcast. - Yeah. - And this podcast will continue. - That's right. - Right, it won't go away. - Yeah. And then my point is that in the future, voice may become the biggest data generator. - Oh, I can see that. - Yeah, so this is why a system, like a meeting knowledge base is so important. It helps you organize all this authentic data content, authentic voice content. Once you've done that, I know you guys are putting into place some agent workflows and such. What kinds of applications could a company do once they have that data stored together and accessible? - There are kinds of applications that the way we look at is just think about the workflows of every role. What's the workflow of a sales wrap or sales manager? What's the workflow on the recruiter? What's the workflow of a product manager, a user researcher? So we think about their workflow. And then once we have this meeting, centric knowledge base, we say, hey, how do we leverage this knowledge base to optimize their workflow? Right, for a sales wrap, sales wrap do a lot of the talking. They talk to customers. One of the tedious job of the sales wrap is actually after they talk to customers is to enter the data into CRM. - For a Vahab's Fah. - And they end a lot of them skip it. - Or do they not? - A lot of them are not very digit. They either complete skip it or just write something random. Then they move out to the next meeting because they're busy. Right, they oftentimes have back-to-back meetings with customers. But that workflow can already be automated. Other actually after your sales call we actually extract the important data or important insights and push that into Salesforce for you. And whatever data you want to extract, you can actually create a template. We have this customized template system. A lot you to say after each meeting, there are several methodologies and MacPake or some other methodologies that to extract data like authorities, customer budget, customer use cases, objections that customers has, competitors they mentioned. And you can configure their template then we can check that inside the push the into Salesforce. Recruiters are similar in the after interview. They need to evaluate. Maybe they have a scorecard, there's five categories, right? You can do that. And those are the external facing meetings. But for internal meetings, we look at our own internal meetings like the product team meeting, engineering team meeting, the project management. There's cost functional, weekly, biweekly sync up, all this data, we can capture that. But then we say, hey, okay, after the meeting, what do you do, need to do next? Do you need to generate document? Do you need to write a email? Do you need to schedule a meeting? Do you need to follow up on the bug? Right? So this is where auditors can do next is to call the right agents to execute some action items for you. And you're doing that agentic connecting in order, right? So you're using MCPs or whatever tools on the back end, but you're doing all of the like, like management of the workflows inside order. Totally, totally. That's why we create a public API, create an MCP server. And we're also building MCP clients. So we can put data from other data sources like Google Drive, Gmail, Slack, Jera, Asana, CRM, then, you know, and you know, correlate that with the meeting data. Right. Again, you know, the volume meeting that's so big and the another advantage of meeting data is actually compared to a written document is usually the most up to date information. For startup like us, where for any enterprise teams, things change really fast. Anything you wrote a month ago, maybe you know, 30% 50% of that already obsolete because things change, a plan change, you know, the customer requests change. But the meetings every day, you discuss the most up to date information. Yeah. So this is why voice data, you know, oftentimes higher weight and the priority. And if it's fresher, and if anything change, it's really important to actually, if you discuss, oh, customer just told us this, we have to do something different. And then if the meeting data, that meeting note is public or shared with other teams, other the marketing team, product team, engineering team, they can all be notified really fast. In the past, and then when things change, you know, that information is not propagated fast enough. So other teams still operate based on the old plan. So that's where a lot of inefficiency happens. So the people who are in the current, who are in the meeting where that decision was made, they know what's happening, they're operating accordingly. But if they miss someone in the shame command, especially like a remote first company, you know, not everyone is going to know that that's the new plan. And that data kind of dies with them. Yeah. Yeah. This is another thing we're building. We call it a leader dashboard and leader workflow. You know, we think about what leaders do. In the early I talk about sales, recorder product manager, but now there's another big role or that's the leader that, you could be a manager at the director managing three managers, or you can be a VP managing, you know, several directors. You know, leaders are tend to be even easier. They manage more projects. They have bigger responsibility. They also manage many people as well. So there's a product management part and there's also people management part. And there's no good tool to help leaders. Actually, we see in end of leaders, again, they spend even bigger percentage of time in meetings. They have even more meetings to go to. And they're often time double box, triple block. One thing we can actually help them on that problem is actually you can send your order meeting notaker to another meeting you couldn't attend. Yeah. Where you still get your notes and gain the information from it still. Yeah. So now, order can take notes for you, but the next step, which we are also working on, is to build an avatar for everyone. So that you can send your avatar to another meeting, which can do the two things. You can tell your avatar, okay, ask of, you know, the VP pro like or ask the marketing guy, there's three questions for me. And if they have questions, you know, answer those questions on my behalf. So your avatar in the future can actually join meetings, ask questions on your behalf and answer questions on your behalf. I'm just imagining a digital boss just showing up at every meeting. What's the ROI? What's the ROI? Right. How could we lower expenses? Yeah, because if you think about it, actually, you know, for some meetings, I usually have a fixed set of questions. All right. But then my avatar can't ask a question. So that's great to the leader dashboard. So. Because the leader managed more projects, so in things that are always updated in real time in meetings, so we're planning to build a dashboard for the leaders so that they can see the real time. Status of each project with the problems, the blockers or anything changed with notified the leaders. And then the leaders can also keep track of, you know, for the people they manage, you know, what are the key things they work on. Based on the meetings they talk, they go, they join or the topics they discuss. So they can give them a lot of data and on the visibility on how their team is performing. Oh, wow, that's awesome. I really like that idea of that. Same. What would be interesting. I don't know how you're going to handle this is like, what if somebody says something in a meeting that's incorrect. Is there a way to like fact check stats and data like to the actual data that's connected in the dashboard. Potentially, yes, we don't do that yet, but it's actually yes. You know, if you can do fact check, if they quote a number, they say, hey, we grow 20% last quarter, but you know, the, the, the order could let go into their database and include the data. It could even like surface that in real time, say, maybe are you sure? Because you know, I just checked the my SQL is at 15% now 20%. One blast in the middle of the meeting. Yeah, that's where I see potentially in the future, the AI note occur actually will become active, not just pass a bit listening, it can talk as well. Wow. Correct me if I'm wrong, your current meeting agent can talk in meetings, right? We actually already built that for business and enterprise customers, they can ask author question, they can say, hey, order, why do we lose that deal? Then it will put data from Salesforce and the key view the answer in real time. So author can already answer questions on the met. It doesn't talk proactively yet. We see the in the future. Order can talk proactively just like another teammate. So basically, we see order will become your AI teammate, not only can take notes, but it can also contribute information in real time as well. Oh, wow, kind of like C3PO, but for the business, right? Where he's always giving you information that you maybe didn't ask for, but could use in a moment and then, you know, just surface it at the right time. Yeah, something I'm curious about as well. With permissions, for example, knowing that sometimes like your leadership may have a meeting that they would rather the rest of the people not be privy to is there a way some kind of a hierarchy in place that. Yeah, there's something we're building as well. You're totally right, not all meetings should be shared with everyone, although there are two things. One is that we have to respect the confidentiality requirement. So we already have a system allow you to configure that in a for this type of meeting you can share it into this public channel, but for this type of meeting only share it to the private channel or for certain meeting you never share when already configure that. And the hierarchical system is you just mentioned is also important we were we're building that system so that we can ingest the organizational chart. You know, say hate the CEO, the VPs, the directors. So we can incorporate that into the system. So there's certain default sharing. And then we can have a hierarchy there. On the other hand, this is where you know culture we see will change in the past, you know, meeting those are really shared with. Even the meeting was not necessarily shared with all the meeting attendees. That needs to be fixed first, but then meeting those are usually useful beyond just the meeting guest. Yeah, often type of contents are useful for a broader audience. Yeah, you want to avoid those data silos. Yeah. So to avoid that, the silos. So that you know we're building that system and also that requires, you know, the corporate culture change in general, I see that the road is moving into a more transparent, more open system. If you think about in the last 10, 20 years, we're sharing more and more in both our social life and our professional life. For social network, right, people share tons of things on the internet. Compared to 30 years ago, people are way more open. And I see that will happen in enterprise in professional world as well. Because the more you share the, the last boundaries. You cut back on the silos and at the same time, you probably increase alignment across a company to ensure that everyone is zeroed in on the same goals and casks ahead of them. Absolutely. I like what you just said, increase alignment. Excellent. You know, with your background in engineering at Stanford and having built the blue dot at Google Maps, I feel like you have a good understanding of like large scale systems. What are what are the current technical bottlenecks and voice AI that maybe people don't realize exist yet or, or do you see anything big coming around the corner? I just want to say, you know, I did contribute to the Google blue dot I wouldn't say I'm the, that's fair. Greater. I viewed the back end location platform, you know, tons of other people built the application. So that's fair. That's a good. That's fair. You know, a little prad in but not so much. Fair enough. The challenges, there's still a lot of challenges. Even, you know, to enders. Well, the biggest challenge is actually to fully understand what people are saying. It's actually hard for human to understand each other. Sure. Then, you know, the, the first problem or the first goal for us is to actually how much can AI understand you? We think we think that AI does have advantage because of the infected memory it can have. It's actually, you know, if, if I'm meeting a, a, a stranger, I don't know too much about that person. It will be harder for me to understand that person. But it was so usually, you know, when I before I meet a stranger, you know, I need to do some background, some chat, right to, you know, I look at this person's link in profile. And I look at, you know, any, any articles about him and the podcast on him, right. So all that tick time. But, you know, I hope, honor can help me do that in the mess before I meet a stranger. The audience will go out on the internet and search for any information about this person. Find the link in profile. So before the meeting, it gave me a brief in the events. It's a, hey, I, a grant, you know, with all the major podcasts, you did in the past and the blocks of road, right. And you link in post you did, you know, it gave me a summary. Yeah. So, so I can really help people to understand each other better. And you might have someone from the, the Northeast, you might have someone from the south, someone in the Pacific Northwest, maybe a couple people who English is their second language, you're dealing with a lot of dialects sometimes in one call. And that seems like a thing that could be really difficult for an AI to keep moving. Or tone, right. Like, yeah, you interpret tone, you know, and someone says something. It's like, are they saying this, you know, in a way that is misinterpreted because, you know, the words don't match the way they were saying it. Yeah. Exactly. I'm an immigrant myself. I still, and I, my accent is still difficult for some people or even for AI to fully understand myself. So that's on the surface, the superficial part, but then the grand you just mentioned deeper issue is the, the meaning. the semantics behind the words. What kinds of people use the same word to mean different things, depending on your background. Totally. And where you come from. So usually more contacts can help me understand each other better. So where do you get the contacts? I think AI can really help you do that. This is where the history that the corporate knowledge base is useful, either even between each department, marketing sales, product, engineering, design. They all have different perspectives, different priorities. They view things differently. So that's where the historical meeting data can help. That being said, they can help people explain why did this guy say this? Why is he concerned about all this? And so this is where I see AI can help people understand each other. In the future, this will still take time. When I'm talking to this VP sales, maybe which was because we have different background, different priorities, it's really hard to communicate. It is. You know, AI could interrupt and say, oh, he have to really mean this thing. Maybe the AI can help her for the other person in a different way so that I can understand better. Oh, wow. I can even see a future where it could proactively recognize spots where say marketing could help the sales team on a thing that may and maybe proactively make a connection between different departments that don't normally visit together or having it give you a quick synopsis of your daily meetings that you did and did not attend. So you could more easily understand common threads and key takeaways and things that you could move on then and be really actionable. Yeah. Yeah, because it has a really good visibility on almost everything that happened in a company, maybe it can explain, oh, there, because there's something else happened like the customer actually sent this and this. That's why the VP sales are concerned about this. Maybe because that VP sales didn't remember using that example, but the AI can help you. Yeah, a brain op that example help you explain better. That's amazing. You see this as a passive experience that happens in the background or an active experience that where it's like I have to say like, is there anything I'm missing here? What do you think? We haven't built that yet. Like just saying that's a potential role that AI can play for sure. Totally. Yeah. Where it's maybe even doing some lot of the synthesis on the back end and kind of putting the pieces together, maybe it has an active synthesis dock that it's working on where it's bringing in insights. Almost like each piece of information that's streamed through the voices could then be put it back out into the larger system and then connections could be made in that like almost like a web pattern. I don't know. You're the engineer. I'm just kind of excited by the idea. I agree with you know, AI can help you connect the dots better. Well, what about so we're like two years earlier point about, you know, kind of reducing these silos from a cultural standpoint. I mean, we're moving toward a future where AI might need access to everything eventually. I mean, there's AR glasses that are listening constantly with meta potentially, ambient assistance in the homes. You've got robots like a, I don't know if you saw the one X and the L that at least for the next couple of years is going to be sending data back to humans and VR headsets. I mean, how do you balance the needs to actually get as much information as possible and like the need for the privacy and the aspects that you mentioned earlier of like, you know, being able to delineate, okay, this person needs this information at this time. How do you balance privacy and utility as well as the developer and the user of these tools in your opinion? Yeah, there are always two sides of the same coin on the one hand security and privacy is definitely important. How do we teach AI to and fully understand what can be shared, what shouldn't be shared. There should be a lot of rules and policy you build in the system. You also allow users to configure the rules and policies. On the other hand, you know, I said, as I mentioned earlier, I see that the world is moving into a more transparent world. Yeah. More and more data being shared. It just a historical trend right before internet things are really hard to share. We're not in a between people, between countries, and people understand each other better. I think that's a good thing, right? So, in a culture, people in different country and different culture can see what the people in other countries are doing. So the breakdown, the wars and the barriers. And again, for teams, right, I already talk about breaking down the silos within the team. I think you mentioned other things like video data and other data. I think that trend will continue. People will continue to share more and more. With certain boundaries, right, people still need to have their own homes and they still have their privacy within their home. And again, more and more will be shared. Both video, picture, audio, other sensor data. I wear my garment. I share my training data on a Strava. So I have a lot of friends who share their running, their cycling. That's just another example, right? Yeah. Biometric. Are you very competitive with that? I run 10 Marassans four weeks ago. I just run the Chicago Marathon. Wow. That's awesome. I really like it. I'm still trying to run a little faster. So it does require a lot of hard work. It does. Totally. Let's fast forward a few years here and what do you think in say 2027, the average meeting looks like? Do you think over the next few years, we're still meetings are primarily humans or do you think there becomes a point where I send my agent over to talk to someone else's agent and they have their own meeting and come back with notes for us when we're super busy. Is that a is that a thing in the future, you think? I think it will happen. It will happen incrementally. Yeah. Right. Again, now many meetings already have AI joining the meeting, taking notes. Again, and AI is still mostly silent today, but in order start to build this on demand agent that can answer questions. And next that would be for the agent to proactively talk, when it sees opportunity for you to contribute, it can start talking. Then there's another staff that everyone of us could have a avatar that can join meetings on our behalf. Then we're joking that in our board meeting that hey, someday, maybe in a couple years, wherever it is, are having board meetings and all of us are just having a drink in a bar or spending time on the beach. It won't happen anytime soon, but it can cover some of the topics between the ever it's ours. You know, that sounds kind of sci-fi, but at the same time, we do delegate a lot of decisions to other people often in business, right? Like maybe your lawyer is going to talk to my lawyer or like, you know, the people under me are having a meeting and then they bring it back to me. So that's not weird. Yeah. It's not that weird. You know, we're also building, really, to that we're also building voice agent that could conduct a sales call on itself. That's potentially right when people visit our website, if they have questions, they want to see a demo in our agent can give them the demo. It's actually live on our website. You can visit our website and we have a comment. actually conduct a visual, a video conference with you and you screen share to show the product to you. And you can ask any question about the product. And also the agent asks you about, you know, what's your role, what are looking for? And if he thinks it's a potential sales speed, you know, ask your, hey, would you like to park to a human agent? So, so the AI can conduct a car by itself. But it's still early. There's still a lot of work to do. That's where you asked me earlier about challenges. A big challenge to overcome is still how do you build the voice agent so that it can conduct a car effectively so that, you know, it can achieve certain objective. It asks questions, answer questions, and maybe, you know, lead the user to convince the user to do something. So, how do you build that agent? You know, part of that is to really model human conversation. We can train that agent by giving it, you know, tens of thousands of sales, if it's a sales agent, for example, you know, it's how a good sales rap can means the customer to buy their product. Then, you know, if you give it enough data, the AI agent could do a pretty good job, too, or can even outperform a human agent. Yeah. Wow. Almost like giving it a decision tree, where it says, okay, if they're concerned about price, this is how we, you know, qualify that or we explain a way, you know, well, you know, this is what you get for the price, et cetera. Yeah. We actually already, another project we have, it's a real-time sales coach. It's actually just basically what you said, if the customer asks some tough questions, if the sales rep is relatively junior, and he will see cannot answer a lot of the questions effectively yet, we have this real-time sales coach that actually surface, it listens to the customer, it hears the objection, and then the sales coach will pop up a answer on the screen in real time. So, if you're doing a Zoom, the sales rep tries to read the answer back to the customer. So, it's almost like cheating in a exam. It reminds me of Cluelie, right, where people will like do that during interviews and stuff. Yeah, we actually, we built that even, they built it. So, it's a part of the order already. Oh, wow. That's awesome. That is. Well, you announced that the order has generated over a billion dollars in customer ROI. What would you say is the most valuable use cases, or most people using it for these types of sales, like reasons, or what would you say? Yeah, a lot of people you can't purchase sales, but others, you know, for customer success, or client relationship, there's one of this, a big financial company, we cannot name it. They use order to handle all the client costs, and they create a channel, a order channel for each client. So, for each client, they have a multi-year relationship, right? So, they actually put all the meetings with that client into that specific channel. And for that channel, they include all the people who work with that with that client. So, that, you know, everyone is informed, and later if they hired a new person who need to work on that client, they just add that person to that channel. So, instantly, the new hire get all the contacts. You can use AI chat to query all those costs as well. So, they found that really useful. We mentioned that in the press release, the customer actually did ROI evaluation. They said, actually, you know, for every 20 seats, they buy it, order can generate a value of one full-time employee. So, that's the result they shared with us. So, we use that formula to ask them, we also heard that from other customers too. Then we use that general ROI formula to estimate how much value our customers are getting out of order. So, that's why we use that $1 billion value. I think it's still relatively conservative. Well, certainly, if you're connecting all of your company's data and you can surface all this information in real time, I mean, that's got to add up like this so much time saved. Yeah, especially then later when the agent can do more and more using agent take away flows. You can tend to even more value, right? It gives some of your action items done for you. Totally. Follow ups from sales calls, for example, send emails to people right away. Yeah. Well, I guess one last question I'd like to ask is, and we often ask this because it's a little bit fun and I think people enjoy it. What excites you most about where AI is headed? And what keeps you up at night? A lot of the things that we already discussed are really excite me a lot. How do we make this meeting set, technology-based reality? How do we get it to update in enterprise which I think will change corporate culture and make enterprise a way more efficient. And then in the future, the the the genetic workflows, the avatars, I think that's really exciting too. It will still take several years, at least several years to make it work well. But it's just a matter of time. It will all happen pretty soon. I would think you know, there's still a lot of challenges to overcome. What do you keep me? It still take time for us to convince enterprises that this will happen and it's better for them to adopt this sooner than later. Because whenever you a new innovative product emerges, it takes some time for people to fully understand it and change their mindset to use it. You know, you even think about the happens to slack. It happened even to zoom or video conference. The early years of video conference, the people who actually you know, double-fuel comfortable showing their face on the video conference. Because the people are used to the phone calls where there's no image. Just to ask the community people to turn on video when they talk, it's a behavior change. On slack, it's like, the slack has some early adoption among startups. But for enterprise, it took them many years to get into enterprises because people are used to communicating with emails. But talking in slack in the channel, because there are many more people in that channel. So talking in front of so many people in the channel is a behavior change. It is. It is. And it's one I welcome. I email is, I still struggle with email and keeping up with it. There's just so much. It's like drinking from a fire hose most days with email. Right. So so honor or meeting no take over with knowledge base. It's still a new new concept for people to comprehend and adopt. So I hope that will happen faster. But we really see that it's start to happen. Are you concerned at all about like the risk of someone's like digital avatar agent going rogue and like, you know, maybe hackers get a hold of it or you know, yeah, it's possible. You don't even want your avatar to disclose, confidential information. Right. Or like say, like avatar of the CEO says, all right, we're giving away hundreds of millions of dollars. Yeah. To this bank account. That's definitely a challenge there. You need to train your avatar to be a, how do you make it a boated proof? hackers won't break it. For sure. Yeah. For sure. Well, Sam, thank you so much for joining us today. It's been it's been great to chat with you and learn more about what you guys are up to at honor. Thank you. Thank you for the thoughtful question. is really excited to discuss all of this topics. - Yeah. - Yeah, great to have you. - Well, to everyone watching, we sure hope you enjoyed today's show. If you don't already, please like and subscribe so we can continue to bring you conversations just like this one today. And if you haven't yet, please sign up for the Neuron Daily AI Newsletter, read by more than a half million others every morning. And that's it for today. Until next time, farewell for now, humans. (upbeat music)