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AI Tone-of-Voice Recognition: Transforming Startups with AI-Driven Solutions

Updated: 5 days ago

AI tone-of-voice recognition is revolutionizing startups, enabling better communication, customer insights, and adaptive education tools.

What Is This About?

AI tone-of-voice recognition is transforming how startups understand customer communication. By analyzing not just what people say but how they say it, AI-driven voice analytics enable more empathetic customer service, better sales conversations, and deeper user insights.

Introduction

AI tone-of-voice recognition technology is opening new possibilities for startups in customer service, mental health, sales coaching, and accessibility. This interview examines how voice analysis AI detects emotional states, intent, and communication patterns — covering the technical capabilities, ethical considerations, and the emerging business applications that are making voice intelligence a viable product category.

AI tone-of-voice recognition detects emotional states, intent, and communication patterns from voice data, opening applications in customer service, mental health, sales coaching, and accessibility. The technology analyzes prosodic features — pitch, rhythm, pace, and emphasis — to extract emotional intelligence from spoken communication. Current capabilities enable real-time sentiment analysis during calls with accuracy rates approaching human-level assessment. The interview examines both the commercial opportunities and the ethical considerations including consent, privacy, and the risk of emotional surveillance.

What Is This About?

AI tone-of-voice recognition is transforming how startups understand customer communication. By analyzing not just what people say but how they say it, AI-driven voice analytics enable more empathetic customer service, better sales conversations, and deeper user insights.


Abstract digital visualization of AI analyzing tone-of-voice, featuring modern tech design with dark blue and gold tones.

AI tone-of-voice recognition is revolutionizing startups, enabling better communication, customer insights, and adaptive education tools. Startuprad.io brings you independent coverage of the key developments shaping the startup and venture capital landscape across Germany, Austria, and Switzerland.

This founder interview is part of our ongoing coverage of Scaleup Founder Interviews from Germany, Austria, and Switzerland.


Table of Contents

  1. Introduction: Why AI Tone-of-Voice Recognition Matters for Startups

  2. The Technology Behind AI Tone-of-Voice Recognition

  3. Applications of Tone-of-Voice Recognition in Startups

    • 3.1 Enhancing Customer Experience

    • 3.2 Revolutionizing Education

    • 3.3 Improving Team Communication

  4. Case Study: Digi-Sapiens’ Journey to Startup Success

  5. Ethical Considerations in Tone-of-Voice Recognition

  6. The Future of AI in Startups: What to Expect

  7. Conclusion: Why Startups Should Invest in AI Tone-of-Voice Recognition


Introduction: Why AI Tone-of-Voice Recognition Matters for Startups


In a world where communication shapes success, AI tone-of-voice recognition is emerging as a transformative technology for startups. By enabling businesses to analyze not just what is said but how it’s said, this technology offers unprecedented insights into customer behavior, team dynamics, and learning outcomes. As more startups embrace AI-driven solutions, tone-of-voice recognition is proving to be a game-changer across industries.

“Startups leveraging AI tone-of-voice recognition gain a competitive edge by enhancing customer interactions and team productivity.”

The Technology Behind AI Tone-of-Voice Recognition

At its core, AI tone-of-voice recognition uses advanced speech recognition algorithms and natural language processing (NLP) to interpret nuances in speech. Unlike traditional systems focused solely on transcription, this technology evaluates tone, pitch, rhythm, and emotional context. Here’s how it works:

  • Speech Analysis: Breaks down audio inputs to detect tone, cadence, and intent.

  • Machine Learning Models: Continuously train on diverse datasets to improve accuracy.

  • Contextual Understanding: Recognizes nuances like sarcasm or enthusiasm.

Startups like Digi-Sapiens have taken this a step further, integrating tone-of-voice recognition into tools that assess reading skills and emotional engagement.


Applications of Tone-of-Voice Recognition in Startups

3.1 Enhancing Customer Experience

Customer satisfaction drives growth, and tone-of-voice recognition can revolutionize how startups engage with their clients. By analyzing caller tone during support interactions or monitoring sentiment in feedback, businesses can:

  • Detect frustration or confusion in real-time.

  • Provide tailored responses to improve outcomes.

  • Develop better chatbot and voice assistant experiences.


3.2 Revolutionizing Education

Educational startups are leveraging this technology to enhance learning. Tools like Digi-Sapiens’ Laletu enable:

  • Personalized Learning: Adapts reading exercises based on tone and fluency.

  • Student Monitoring: Tracks progress over time with detailed reports.

  • Inclusive Education: Supports diverse learners, including those with accents or speech challenges.


3.3 Improving Team Communication

Effective communication is the backbone of any startup. Tone-of-voice recognition tools can:

  • Evaluate how team members interact during meetings.

  • Offer feedback to improve public speaking and presentations.

  • Identify potential conflicts through tonal shifts, enabling proactive resolution.


Case Study: Digi-Sapiens’ Journey to Startup Success

Digi-Sapiens, the 2024 Frankfurt Forward “Startup of the Year,” exemplifies how tone-of-voice recognition can drive impact. By developing innovative AI tools, they addressed critical challenges in education, such as declining reading proficiency and teacher shortages. Their success underscores the importance of:

  • Identifying real-world problems.

  • Building scalable solutions.

  • Partnering with key players in education and technology.


Ethical Considerations in Tone-of-Voice Recognition

As with any AI technology, tone-of-voice recognition raises important ethical questions. Startups must address:

  • Data Privacy: Ensuring sensitive audio data is securely handled.

  • Bias Mitigation: Training models on diverse datasets to avoid discriminatory outcomes.

  • Transparency: Informing users about how their data is used and analyzed.

By adhering to ethical practices, startups can build trust and foster long-term success.


The Future of AI in Startups: What to Expect

AI tone-of-voice recognition is just the beginning. Startups can look forward to:

  • Multilingual Support: Expanding capabilities to include non-Roman and tonal languages like Chinese and Arabic.

  • Deeper Emotional Insights: Understanding complex emotions for better customer engagement.

  • Seamless Integration: Embedding tone-of-voice analysis into everyday tools like CRMs and project management software.

Startups that invest in this technology today are well-positioned to lead the market tomorrow.


Conclusion: Why Startups Should Invest in AI Tone-of-Voice Recognition

For startups, AI tone-of-voice recognition offers a unique opportunity to innovate, improve, and scale. From enhancing customer experiences to revolutionizing education, this technology is a must-have for forward-thinking businesses. By embracing tone-of-voice recognition, startups can unlock new levels of efficiency, empathy, and engagement.

Resources


Learn More


If you are looking to understand the rise of AI and deep tech startups in Europe, including how emerging technologies like machine learning, quantum computing, and robotics are transforming industries, you should not miss Europe’s Ultimate Guide to AI & Deep Tech Startups. This in-depth resource provides founders, investors, and ecosystem leaders with a comprehensive overview of European AI innovation, venture capital trends, and deep tech opportunities, making it a must-read for anyone aiming to stay ahead in the fast-growing European startup landscape.

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  • Jörn "Joe" Menninger → Host of → Startuprad.io

What is this article about: AI Tone-of-Voice Recognition: Transforming Startups with AI-Driven Solutions?

AI tone-of-voice recognition is revolutionizing startups, enabling better communication, customer insights, and adaptive education tools.

What are the main takeaways from this discussion?

AI tone-of-voice recognition is transforming how startups understand customer communication. By analyzing not just what people say but how they say it, AI-driven voice analytics enable more empathetic customer service, better sales conversations, and deeper user insights.

How does this topic connect to the broader startup ecosystem?

AI tone-of-voice recognition technology is opening new possibilities for startups in customer service, mental health, sales coaching, and accessibility. This interview examines how voice analysis AI detects emotional states, intent, and communication patterns — covering the technical capabilities, ethical considerations, and the emerging business applications that are making voice intelligence a viable product category.

About the Host

Joern "Joe" Menninger is the host of the Startuprad.io podcast and covers founders, investors, and policy developments across the DACH startup ecosystem. Through more than 1,300 interviews and nearly a decade of reporting, he documents the evolution of the European startup landscape. Follow Joern on LinkedIn.

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Automated Transcript

1 Hello, and welcome, everybody. Guys, it is getting close to 2 Christmas. This is Joe from Sudapri. Io, and therefore, I'm bringing 3 you a very special bonus episode this week 4 to you very shortly before Christmas. But nonetheless, I would 5 like to welcome Daniel here. Hey. How are you doing? 6 Hey, Jan. I'm doing well. Thanks. Thanks for having me. 7 AI pleasure. We may tell our audience that this, recording 8 is sponsored by Frankfurt, meaning the business development 9 agency who is also supporting Frankfurt Forward. And 10 the reason you are here, you guys won start up of the 11 year 2024. Congratulations 12 to that. Did 13 this recognition first, can 14 you tell us a little bit about you and your company 15 before we get into the specific questions? Yeah. 16 Sure. Yeah. So 17 Daniel Iglesias is my name. I am from the AI Main

18 region. I AI married to teacher. My 19 professional background is in banking technology consulting. 20 That's what I did before I founded, 21 Digisapiens in, 2020. 22 And, what we do at Digi DigiZapiens is 23 we produce speech recognition systems 24 that not just recognize what is being 25 said, rather how it's being said. So 26 it's a speech recognition system that is geared towards 27 special use cases, that 28 are relevant to measure how well somebody speaks or 29 reads. And with the help of this speech 30 recognition technology that, is AI, 31 so that we've built ourselves, you can build 32 use cases in especially in the area of 33 education. So that's where we started. And the first use 34 case that was built with our speech recognition technology 35 was the LALI 2. LALI 2 36 stands for loud laser tutor in German, which is,

37 reading aloud tutors. So it's it's a tool, 38 that listens to students in schools 39 from 2nd to 7th grade in Germany. 40 While they read aloud, it analyzes how 41 well they do that, so it carries out a diagnosis. 42 And after that diagnosis, they are, 43 being trained to become better readers 44 based on the, diagnosis that was carried out before 45 that. So basically, AI looking for a question here. Sure. 46 When you said they are your tool 47 helps, how well they are speaking 48 their AI the tone of voice recognition. Is it only 49 how well they vocalize the tones? Or is 50 it also that you can deduce some some 51 level of their understanding of what they're reading? 52 The speech recognition technology itself is, 53 audio technology, so it listens. So we it detects everything 54 that can be caught by a microphone.

55 And, in contrast to, I 56 call it, regular speech recognition systems where the goal is to 57 detect the probable intent. So what would 58 be this what are you probably meaning? So, 59 the goal is to carry out a a 60 task or, AI I'm 61 looking, a command. You have to carry out a command. Mhmm. Yeah. 62 Play this and that song or whatever. In contrast to 63 that, we really transcribe and list listen to what has 64 actually been said. So this includes 65 arrows AI my that I already said now a few 66 times. And repetitions, or 67 text so regarding text repetitions, things that have 68 been left out or added, the tonality 69 of things, and also whether you pronounce words 70 correctly. Yeah. So that's what the, speech 71 recognition technology does. But we also develop, 72 systems that help understand help

73 students understand the text better by 74 generating, 75 differentiated quizzes. So, you cannot ask 76 every reader the same question. It must be adapted to 77 his reading level and also understanding 78 capabilities. So the complexity of the questions 79 and the possible answers also must be adapted. So, 80 all in all, we're in the business of providing 81 education, specialists, with, 82 with the necessary tools to build very innovative 83 adaptive tools, for learning 84 reading skills or language 85 skills? That is exactly what I had in mind. 86 Vividly remember when, for the first time 87 in my life, I understood a Chinese joke 88 about foreigners, instead of how 89 how, she said, how how. So the the 1 means 90 good good, the other means mouse mouse, different tones. So the the 91 the the question is here, how 92 many languages can you do? And isn't something like

93 Chinese where there's a different if I ask or 94 the 1 we means please ask. So if you ask for direction, 95 the other one's the other 1 means please kiss. Well, I made 96 an older Chinese lady on the streets of Beijing really blush. 97 How many of those differences could you actually do? 98 Because on the top of my mind, yes, of course, English is a little bit 99 difficult to pronounce Spanish as well. But if the tone really makes a 100 difference, like in languages, like Chinese, Cantonese, and so on and so forth, 101 that would weigh your AI way 2 would really come 102 in handy. So my question would be, how 103 much can you do there? Could you, give us an 104 idea of the granularity and languages you cover? Yes. 105 We so as of now, we're covering German and English.

106 We did not experiment with Chinese since the 107 Chinese education technology market is highly regulated 108 and basically close towards foreigners. 109 But, we my team, I have 110 dedicated experts in, 111 working with non Roman 112 languages, so especially also Indian languages. 113 There's 40 something. Sorry that I cannot recall 114 the exact number, but there's, more than 40 115 languages, official languages spoken in India. We can work with 116 those. We can also work with, Arabic 117 character sets. But as of now, in terms of 118 solutions that are at hand, we can work with 119 Germany, German language, and, we 120 or next year, we will also launch, the English version 121 AI API, and other languages. 122 We have the skills and capabilities to train and 123 fine tune models, with a short pilot 124 project that we need to carry out with potential customers.

125 So that means you already, by the way, I linked it in the show 126 notes. La Lalu. Who is it? 127 La la la la la la la la la la la la la la la 128 la la la la la la la la la la la la la la la 129 la la. It's There's a there's a, a 130 song that you sing to children before they go to bed, 131 AI. It's called. Yeah? 132 And, we have some similarities there. So it's called 133 too. It's about 3. Mhmm. 134 So, sorry. Just 135 typing here, that we also linked the 136 song here, in the show notes. My my quest 137 so this already establishes something we 138 could deduce from what you're saying. So, basically, you are 139 not a customer facing product. You're 1 of the tools, the APIs, 140 others could include, could work with in

141 developing their own client facing b to b, b to c, b to 142 g tools. Right? Yes. 143 With the asterisk, we we have 144 developed the LALI 2, for our partner at hence, 145 So we do develop platforms and applications, 146 but we rather license our the speech technology 147 to partners, b to b, b to g, b to c, whatever. 148 We are already discussing, the tool. But 149 before that, I I actually wanted to be because I have so 150 many questions. Before that, I would actually, wanted 151 to ask you 152 where this idea is coming from. I do believe I have an idea since you're 153 married to your teacher, but you have been working in banking, 154 finance, technology, triangle consulting. So 155 so, where did the idea come from? How did you get 156 that? And especially the question, when did you decide

157 jump ship to really do this full time? 158 Okay. So I was, like you said, I 159 was about 17 or 18 years into banking technology, 160 and, I always had the goal 161 to promote young people 162 in achieving, how do you call 163 it, higher education. Let's put it this way, to 164 get the most out of their potential. So I did, 165 trainings in schools for how to apply to a job, 166 how do I choose the right job for me, etcetera etcetera. And 167 I always had this passion for helping young people. 168 So, that's that that passion was always there. But in 169 2019, that was the time where I really, 170 thought about what can I do with the skills that I have and the 171 knowledge that I have? And, to to really have an 172 impact on our youth in a bigger scale. Because

173 this is the AI, shortly after AI became a father of 174 a of a daughter, and I have observed 175 certain trends in our society in Germany. 40 to 176 50% of the children have 177 background, with non German parents or migration 178 background, as you would call it in Germany. And this 179 leads to some hurdles and 180 some difficulties, in, 181 in the school system, and and and since 182 we also, at the same time, have a shortage of 183 shortage of teachers. And I have also 184 observed what happens in the market regarding 185 the upcoming AI of AI, robotics, automation. 186 I was part of it in banking. So I added 187 the deterioration of reading skills 188 towards higher requirements 189 regarding job skills and came up, 190 with, with a 191 perspective that I didn't like for the future of my children. So that's

192 why I decided to take my skills, 193 which is general management, business 194 development, technology understanding skills, and 195 work together with the best experts I can find, 196 in terms of reading capabilities 197 and, reading training and, 198 excellent techno technology experts bring those things together and 199 build what you find today. 200 Mhmm. The tone of voice recognition 201 is fascinating. You already told 202 us the, loud reading tutor is 203 something you develop for a customer. Could you also 204 share another example already where an external, 205 client is using your tool? The 206 second example is in the making. It's not ready to be 207 shared publicly, but, I must openly say the 208 past was, highly, 209 we were highly invested into building 210 that tool, which is 1 of a kind. It took a lot of 211 attention and all of our resources to get it running in

212 time and, make it 213 scalable and stable and user friendly. So 214 now that the product is fully marketable and 215 most of the almost all bugs are fixed, yeah, 216 now we are able and ready to focus in on 217 new, projects and partners. 218 AI see. Talked about 219 partners here and winning new clients. Winning the Frankfurt Forward award 220 is a huge accomplishment. What do you think made DigiSapiens 221 stand out among the competition this year? 222 AI think it's the social impact, 223 dimension of what we're doing. We are for profit social enterprise, 224 so we are here to do good 225 and, earn some money at the same time. And I think the audience 226 AI that idea, and I think there's a lot of ad 227 techs out there, but pulling it off in the way 228 that we did, by partnering with such a,

229 renowned brand AI Ernst Kedfalak, 230 as a first initial project. And at the same time, 231 building such a unique technology like we do. 232 I think that's what impressed the jury and, 233 caused a lot of, support in the audience. 234 I see. I see. Your 235 technology has potential across industries. 236 We already know you're working and focused 237 on the education, but could you also see some other 238 industries where you could, like, in the future, a few years down the road, 239 apply it? 240 Yes. Outside of, education, 241 there is also the entertainment and gaming industry 242 that could work with our technology, 243 where you could you could use it to build games that, 244 based on reading skills, which would 245 be some sort of, yeah, educational games at at the same 246 time, but you can also use it to,

247 to build, how do you call it? 248 A a presentation trainer or speech trainer that, 249 helps you become a better speaker for public speeches. 250 The creativity and opportunities are unlimited, 251 but everything that involves the ability 252 to carefully listen to what and how things are 253 being said. You know? Mhmm. 254 I AI was wondering, AI sure you 255 thought a lot about potential use cases. Could you share, like, 256 the the the the the the most interesting, the most, 257 quirky 1 you already came up with? 258 No no need that it actually AI, but you thought, 259 theoretically, our idea could also be applied too. 260 Yes. So we have applied it to reading 261 learning or reading promotion, but, very, 262 very relevant use cases also in the area 263 of language learning. You have seen 264 big companies like Bubble, etcetera use it in

265 some way. Yeah. And we envision 266 other ways that are much more focused on 267 dialogues, that our technology could be 268 used for to promote language skills or learn a new 269 language. So we are able to evaluate how 270 things are being pronounced. That's 1 major skill. We can 271 analyze, literally what has been said. 272 We can analyze 4 ds, all areas 273 of, language that we can analyze. 274 And I think this is relevant if you want to learn a language 275 properly. You have, you have given some example from 276 Chinese. If you listen to people 277 talking German with all their accents and 278 dialects, we also have ways to 279 tackle, dialect, 280 dialects because the way you use your mouth, your 281 tongue, your teeth. So your 282 complete speech apparatus is also something that we can

283 derive from the audio signal and combining all 284 those, all those measurements 285 into a cohesive didactical 286 concept is something really unique, 287 that we haven't seen so far. Mhmm. 288 Going into a little bit different topic because every everybody talks 289 about accuracy, like fantasizing AI and 290 ethical use of AI. With analyzing of tones, you're 291 you're, collecting potentially 292 sensitive information or your clients do and you process 293 this. How do you, ensure 294 the ethical use and the accuracy when handling the sensitive 295 data? Yeah. So 296 the in Germany, it's always a relevant question whether it's a 297 personal personality AI identity related data. 298 You know? That's 1 major question. And, 299 the the thing is, if voice 300 really is such data, you would 301 need to have some registry 302 of confirmed identities 303 that are linked to a voice profile or voice biometrics profile

304 to to pose some danger 305 to a data leak or whatever. You know? Mhmm. 306 And this is not the case and will never be the case. We will 307 I well, let's let's not say it will never be the case. I don't know 308 what happens in, the year 21 100. But as of now, we don't 309 have a voice register, a public 1. 310 And, the question is also, even if this existed 311 on a government level, the question is also, do 312 companies, do other individuals, 313 criminals have access to this registry, and can they use it to harm 314 you? And the I don't I don't see 315 that. When you ask me about ethics 316 in my context, we regard the topic of 317 ethics in terms of accessibility to 318 our solutions. So can somebody from Bavaria 319 use it, as the same way as somebody from

320 Saxony can use it? And can somebody 321 with Turkish or Arab 322 accent use it AI somebody from, Hanover 323 without any accent? And the answer is yes. 324 So we AI to and we put a lot of 325 effort into avoiding any biases 326 in our speech recognition system by 327 training it very profoundly 328 with different accents and dialects 329 to make sure that it works with every 330 user. Yeah. So that's how we look at that. 331 So you you you put a lot of effort into that, 332 making it possible for everybody to understand. We may tell the 333 audience that there are some people who speak very, hefty, 334 local accents, not only from Bavaria, but AI, 335 Thales, Saxony, and so on and so forth, but also Platych 336 in the very north. It's really hard for you to understand when you're from a

337 different area. Many Americans will understand, 338 will, have an idea when I talk about somebody with a very 339 heavy southern draw or something that's also hard to understand. So 340 you took care to cover all those 341 peoples and not disqualify somebody there. So I do believe there 342 was a lot of development work going into. 343 What challenges did you face, and how did you overcome this in 344 developing digital DigiSapiens, not digital. 345 DigiSapiens. Sorry. Yes. So 346 yeah. There there were a lot. So which 1 can I 347 yeah? So we started as a company that wanted 348 to provide speech recognition systems only, 349 And then we were suddenly in the position to develop a whole 350 platform. So in a short time, we had to 351 set up a team that was able to do that, build a 352

product team or, UX and 353 front end development team around our core technology 354 team in a very short time and, 355 build a product that fulfills high 356 expectations. And this, was a 357 real challenge. To be honest, we, 358 like a lot of other startups, were 359 in the forced to publish a product a 360 year ago that was not perfect, far from perfect. 361 So we got that feedback in the beginning, but we worked 362 really, really hard, 363 with our team, which also includes the first level 364 support who's directly in contact with us, our schools, 365 that use it and the partners to really get the first 366 hand impression of what is 367 working well and whatnot, and they are 368 very much integrated into our development process. 369 And we take we took every feedback very 370 seriously. And, yeah, now a

371 year after we've launched, I am confident to say that 372 we have a very unique, innovative, and highly 373 effective, reading promotion solution 374 that is, yeah, that we can 375 be really proud of. I see. 376 The AI world is developing pretty rapidly. You 377 are right now, I would say, on the cutting edge of development. 378 How do you make sure that you remain 379 there as 1 of the top solutions keeping up with the with 380 the AI developments? We 381 thanks, for that feedback. Yeah. And we and 382 I, we really work hard to be seen this 383 way. So what we do is we invest a lot a 384 lot into r and d. Most of our money goes into r and 385 d. We publish papers. We participate 386 in international conferences, where we 387 also do take over

388 tasks and compete against other teams 389 in optimizing models, quantifying models, and 390 raising accuracy. And we always, come 391 up on top, also, leaving 392 huge names behind us. So we, 393 we regard this as a sport to develop 394 new methods, overcome, 395 overcome hurdles 396 and, yeah, really try to be on the cutting or beating edge 397 when it comes to sophisticated speech recognition 398 and NLP solutions. Yes. 399 Daniel, I'm sure there will be questions on 400 where are the papers. I do have a few suspects where you mentioned something like 401 this. You will give me after the official end of the 402 interview, you will give me, the link, and I'll post it in the show 403 notes. I do have a few certain suspects that always request something 404 like this. Yes, Claude from Paris. I'm looking at you. Exactly.

405 And then they they can dig through it. So, 406 let us go into the very last part of the 407 interview because I'm now already bothering you for, like, 408 almost 40 minutes in this online meeting and, 409 more than 25 minutes in actual interview. So, 410 don't worry. There there are only a few more questions left. 411 I was wondering winning an award like Frankfurt Forward often 412 reflects strong local support. How has the 413 Frankfurt ecosystem contributed to your journey so far? 414 There are a lot. 415 So the our ecosystem is 416 very regional. Our investor is regional. Our 417 network helped us find our first customer, 418 is from the region. I we get a lot of 419 recognition and inquiries due to that, price. 420 So, it's mostly visibility 421 and also recognition. So it's when you approach somebody 422

and, he asks you who you are, what you do, and, 423 you mentioned the start up of the year world from Frankfurt forward, 424 especially in the region. Everybody stops questioning 425 whether you are or whether what you are doing is 426 sound and makes sense. So, 427 the intro and entrees into conversation building partnerships 428 is much easier. Mhmm. And 429 now only 3 more questions left. 430 You are AI now a leader in a very specialized niche in 431 AI. But what advice would you offer to other start ups 432 looking to innovate in the AI and tech space? Some kind 433 of skills, like processes you have learned so far, 434 not only taking the, your business ideas from influencers 435 on Instagram. Yeah. 436 I don't know if I'm the right 1 to give advice. Yeah. I'm not, 437 the tech guy in my company. But what I would generally suggest, when

438 looking at tech is not looking at a hype or the technology, 439 but rather trying to solve real world problems. 440 So AI in Germany, we have 25% of the children, 441 that at the age of 15 do not understand what they 442 read, and they don't understand what they read because they are not fluent 443 in reading. So that's a huge societal 444 problem, and that's, that was the initial thing 445 that led me to found it found DigiZapiens. 446 And I would really not focus on the 447 technology or the AI for the purpose of the technology in 448 AI, but rather using tech as a 449 means to solve a real problem. Yeah. And if it takes 450 AI, it's fine. If not, not. 451 But 1 also has to say in German, there can 452 be very difficult, 453 sentences and structures. III

454 everybody who's who tried either in German or in a 455 translated version to read Kafka should know what we're 456 talking about here. So, therefore, it 457 can be difficult. There's a saying in German, 458 German language, difficult language. So, actually, 459 it it it says good things about you guys that you started 460 with the German language and mastered it for your, for 461 your, tool, DigiSapiens. 462 We usually close out with 2 more questions, and they're usually 463 pretty simple and usually end with a yes. But I'll ask them 464 anyway. Are you open to talk to new investors? 465 And as always, I'll link your LinkedIn profile down here in the show 466 notes wherever you're looking this wherever you're watching this. No. 467 Sorry. This AI, no watching. But, 468 anyways, you you either directly in your tool. I'm 469 sorry. Not every tool allows links you can then click.

Want to reach the DACH startup ecosystem? Become a partner and connect with founders, investors, and operators across Germany, Austria, and Switzerland.

470 So, basically, you could go to our blog, standard break. 471 Ioforward/block, and there we link Daniel's 472 profile. Plus, when you are 473 expanding, when you're growing as a young company, I am sure you're 474 all so open to have applications from potential new 475 employees. Right? Yes. Yes. Yes. Yes. Yes. We're 476 looking for we're looking for good people always. 477 AI, is there a career website that I could launch, 478 or should the people simply, that I could link, or should the 479 people, simply reach out to you via email? 480 Yeah. The latter. Directly reach out to us. We, 481 we could, we we have a way to go regarding an 482 HR department, so everything's handled by the team, depending 483 on the competency somebody's applying for. So 484 can't use the public channels or directly contact me, and I will forward

485 it to the colleagues. Again, go to the blog to the LinkedIn 486 profile. Guys, it was a 487 pleasure talking to you, Daniel. Thank you very much. Thank you very much for 488 answering more than 30 minutes difficult questions here and, 489 keeping up my stupid interjection interruptions. Thank you very 490 much. Thank you. Nice being here. 491 Yeah. So and yeah. Thanks for having me here, and, yeah, 492 Merry Christmas and a happy New Year to everyone. 493 Thank you. Yeah. Merry Christmas. Happy New Year from you as well. 494 Thank you, guys. Bye bye.

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