A (3:16)

Thank you. And I appreciate that, you know, you started from the ground up and just rethought the whole process. And again, having that innovative mindset certainly helps. But yeah, 2016, 10 years ago, just about. It does seem like a decade or a universe ago, as you said. I really like talking to entrepreneurs. Founders that really roll up their sleeves, jump in and say there is got to be a better way. Better, faster, smarter, cheaper is the way they say it. But I appreciate the backstory that. Brian Boostlingle reportedly grew by 50% or more each year and now supports over 17,000 interpreters and 160 employees. What strategies, culture or innovations fueled that sustainable hypergrowth?

B (3:55)

That's a really good question and I could probably talk for 20 minutes on this topic, but I won't do that. I mean, I think if I kind of narrow it down to some of the, I think the most important lessons I've learned as an entrepreneur early on about running a successful technology startup. You know, I think number one, you've got to have a clear mission and well defined quarterly objectives. I would argue even in the pre revenue stages of a startup, you know, most people think about like early, early stage startups as just total chaos, people wearing multiple hats. There is no structure, there's no design. Everybody's trying to be all things to all people. But I think focus, even in those early days is really critical because it's so easy to get distracted by, I guess, enticing opportunities that appear along the way. You know, think about when you're early stage startup and you see large customer opportunities, you're really asking them, you know, how high do I jump? Like what, what can I do to please this potential prospective customer? You end up going down rabbit holes, chasing these large customer requirements in the hopes of building some features that might generate quick revenue. And I think we were really disciplined early on. Of course we made some mistakes. There were definitely some punch holes in the wall moment, at least figuratively. But the way to avoid that trap, I think again is staying grounded in your mission. And really aligning around a product roadmap that everyone, all stakeholders, commit to. So for us, for example, in DOS lingo, we could have built a bunch of translation features, which is very different. Translation technology is very different than interpret technology, for example. But we were disciplined not to go do that. Even though several of our customers were asking us to do that. We knew that we had to stay focused on the interpreting workflow early on. Otherwise that distraction. You try to do too many things and you won't do any of them well. And so I think if anything surfaced, you know, outside the scope of these goals that we were focused on, the answer had to be no. And we got better at saying no as time went by. But I think a lot of startups don't do that, and then they really struggle. And then I think another principle that served us well, if I think about it, was really cultivating what I call a bottoms up culture. We really focused on hiring people who could teach us. Not, you know, hiring people to just tell them what to do, rather hire people that would tell us what to do and challenge us and really guide the direction of the company, rather than simply waiting for us to tell them what to do. And so by creating this sort of inclusive environment where trust is given, not earned, right? We hire people because we trust them to do their job. They don't have to prove it to us. I think that we built the conditions for our employees to really thrive and innovate. And I think one thing that we keep track of is a KPI called enps, right? An Employee Net Promoter Score. How happy are your employees? Are they learning? Are they developing? Are they thriving? And we have always been sort of off the charts on that metric. And that's a really key metric because you don't have employees leaving voluntarily, right? They really love working at Boost Lingo. If you hire the right people and they love working for you, you know, things are going to go well.

A (7:05)

That's awesome. I appreciate that. And I highlight just a few things here. Some of the most important lessons you learned as a tech entrepreneur is having that clear focus, well defined goals, that mission, right? Especially early stage, making sure everybody's aligned, committed to the same vision, you know, having discipline to stay focused on your core product. Right? Your core vision. And then that bottom subculture I think is important, hiring the people, as Steve Jobs said, you know, hire really good people and get out of their way, let them do what they do best. So I appreciate that. Brian, the next question I have for you, you've commented on Common misconceptions about AI telling us AI won't replace interpreters but instead expand their capacity for complex work. How are you integrating AI thoughtfully into your product suite without undermining professional interpreters?

B (7:48)

Wow, this is such an important question and it's something we think about a lot. Right? You should take a step back. I mean, this is an exciting moment of rapid technological change. I think you and I can agree on that. Things are changing rapidly. And when you think about Boosinga's mission, which is really to expand language access through technology innovation, these remarkable advancements in AI really feel like at least to be a dream come true. I mean, they open up new possibilities for breaking down language barriers and making language services more accessible than ever before. You know, just recently I was reading in the United States alone, more than 60% of limited English proficient individuals, what we call in the industry LEP in the United States, they lack access to professional interpreters during critical and regulated conversations. So those are conversations with their attorney, their banker, their doctor.

A (8:40)

Right.

B (8:41)

They don't have access to an interpreter In 60% of those interactions. So it's better from our perspective to have AI access than no access. And if you consider sort of the patient journey in a large healthcare system, right, in the United States, that's a complex healthcare system that we have. But a patient might have access to an interpreter when they're meeting with their doctor, right at point of care. But what about when they're getting their intake done in the reception or they're calling in to schedule their appointment? We've all gone through those ivr, those sort of landline menu systems, right? Press one for Spanish. But what about Haitian Creoles or what about Arabic or all these other languages? Right. They don't have access to any help in setting up their appointment and going through those intake forms. So there's really a language desert and AI can fill those gaps. And so that's a big win for us because again, for us it's all about breaking down language barriers. And technology innovation is going to help us break down more language barriers than ever before. But that doesn't mean that AI is going to replace human interpreting. There's something that we talk about a lot at Busingo called the decision tree that we help kind of walk our customers through. And you know, when should you use AI and when should you use humans? And you know, it's kind of on this scale of low complexity to high complexity and low risk to high risk. Right. If you're in a high risk, high complex conversation Right. You're talking to your doctor about cancer treatment and it's a highly complex conversation. You're not going to want to use AI for that. First of all, it's a very high risk, right? And even to this day, with all the advancements in AI for most languages, AI is only about 95% as accurate as a professional human interpreter. But for low risk, low complexity conversation, it makes a lot of sense to use AI. So again, a lot of our customers are cautious about relying on speech to speech AI in high stakes, critical conversations. And I think they should be. But you know, those same customers are ready to embrace AI when it enhances rather than sort of replaces interpreting. For example, a lot of our customers are asking for things to enhance their interpreting experience. They still want a human interpreter, but they want a meeting transcript and a summary that will feed into their medical records system. They want real time captioning, you know, to tell them on the screen what is being conversed. Or they may want like language detection tools because it's an emergency room and the patient just came on a gurney and they don't even know what language they speak. Right? AI could do language detection. So there's lots of really cool things that AI can do to enhance that. But the bottom line is we really don't see AI replacing human interpreters anytime in the near term future. Because people that are familiar with the job that a human interpreter does, understands the nuance, the emotions, things like sarcasm, those emotional inflections in language can be very hard for AI to pick up and get. Right. So our belief is really simple, AI where it fits and human when it counts.

A (11:47)

Thank you, Brian, I appreciate that. I agree with you. Right now, AI can only make this human process, human interpreters better at this point. Obviously AI can fill in the gaps like you had mentioned, manage some basic intake forms, fill in those little gaps, I believe, and in what I heard is this AI human partnership is helping to really break down language barriers. And you did highlight high risk versus low risk, high complexity versus low complexity. And that's where you kind of say, okay, a human is needed for this versus a machine and vice versa. So I appreciate that, I really do. Brian, the last question of the day, as we look ahead, how do you see language access evolving, especially in areas like intelligent routing, AI captioning or enterprise expansion?

B (12:31)

Yeah, it's. For me, AI is here to stay, right? This is not like a short term fad. I think we could all see that it's having a lasting impact in as somebody who works in A technology company. I don't just use AI as a Google search bar. I use it as a mentor almost. And there's a saying, AI is your os. It becomes sort of integrated into your everyday work. And I think as that continues to happen throughout society, it's going to rapidly evolve and change industries completely. And we're no different, right? The only thing I know for sure is that if Boost lingo doesn't change rapidly, we won't continue to grow rapidly. And we're constantly reminding our team of this. I think you're going to see things like, for example, we have a call routing algorithm right now that we could put AI in the call routing algorithm to make more intelligent decisions around how we IT browse calls to which professional interpreter. It could help us reduce response times. You know, we already have really fast response times, but it could make it even better. It could enhance quality. Right now we have thousands and thousands of interpreting calls that go through our platform and we have to have humans review the quality of those calls. Every single call we have to review to make sure the interpreter did a good job. AI can help us streamline that. AI can actually test quality and allow us to quickly figure out which interpreters may need to be retrained. So that's just one example. AI captioning is going to become more important. One of the languages that we support is American Sign Language, right? For the deaf and hard of hearing community. But think about all the old older Americans who, you know, they've lost their hearing and they don't know American Sign Language, right? So when they go to the doctor, they just can't hear. And so imagine how powerful real time captioning can be, right, where when the doctor talks, they can at least read what the doctor's saying in real time. And you don't need a professional human transcriber out there typing in the captions. That's why you actually see a lot of these AI captioning startups raising a lot of money. And I think the winners here, there's a lot of AI companies, right? Trillions of dollars invested in venture capital into AI startups. So who wins in the long run? And one of the parts of your question was enterprise expansion, right? We believe the winners will be the ones that have the best user experience and that create competitive moat. In other words, it's a workflow, not a point solution, right? If you think about Google Translate, right, That's more of a point solution. I'm at the restaurant trying to order sushi. I use Google Translate to help me translate a single sentence. But if I'm in a hospital and I'm a patient, I don't just need to have AI interpret the conversation. I need that meeting summary, I need that transcript. I need it fed into the EHR system that the hospital uses. So there's all of these additional workflow aspects that make the software more sticky and that workspace is extremely important. So again, I think that AI is going to increase GDP dramatically and it's going to create thousands of successful startups. It's going to make a lot of people a lot of money and it's really exciting to work kind of on the forefront of this in our industry. You know, I feel like it's almost like we're a startup again. Even though we're continuing to grow, we're adding more employees. You know, it's exciting to work on this new technology that we know will add value to our customers.

A (16:05)

Thank you. I appreciate that. And sharing your insights of where AI is going and how it's being used today and highlighting a couple things. I think AI is certainly there, as every entrepreneur and founder knows that you've got to continue to improve your platform and service to stay in business and AI can certainly help augment that. I liked how you said AI can do a lot of the QA now. I think that's important. It takes humans out of the mix to do higher level tasks. The one thing I definitely took away on this AI captioning is we do have a large population of elderly that don't know sign language and they're hard of hearing. And this real time AI captioning is certainly a great use case. So I appreciate you sharing that with our audience today. Brian, it was certainly a pleasure having you on today and I look forward to speaking with you real soon.

B (16:48)

Thanks Brian. It was a lot of fun. Thanks for having me on.

A (16:50)

Bye for now.