Hi, everybody. Uh my name is Wendy Gonzalez. I'm the acting CEO of SOO uh as well as president of SOO. And uh I'm here to share a little bit about what we do and how we are changing the world through A I and training data.So um a little bit about ourselves. Uh Soo provides training data software and solutions to 25% of the fortune 50. Um We help companies like Walmart uh and Google as you can see here, bring their artificial intelligence solutions to market through our training data solutions.

And uh in 2019, I'll talk a little bit more about training data. We had over a billion points of annotated data and um we are are sitting at about 25 million in revenue. So uh let me share with you a little bit. What is training data? So training data um is, is basically before a machine can learn how to see, hear or speak, it needs to be trained with labeled data. So for example, a self-driving car as you can kind of see in this screen over here, um needs to be trained on how to see a vehicle a pedestrian uh lanes, road signs, et cetera. So as you can imagine, while nearly $100 billion according to I DC is going to be invested in A I by 2023. Um training data of that 100 billion. Uh it can't really be realized without training data. Um Training data represents uh 80% of the time consumed in most A I and machine learning projects. And the majority of projects run into problems with data quality and labeling. So at the end of the day, we can't have artificial intelligence models without training data. So that is what we do is we provide uh training, data, software and solutions. Uh But now what I'm gonna do is share a little bit more about um the why we do what we do. Uh We are a mission based organization.

Uh We have a very specific purpose. Um We were founded in 2008 by our late founder uh Lila Jna and I'll share a little bit more about her later. And our belief inherently is that talent is distributed equally while opportunity is not. And we believe that the best way to move people out of poverty is by giving work instead of giving aid. This is a picture of Ken Kihara. He's actually part of our, our team and staff and it's with his daughter here in Mathare uh which is one of the largest slums in Kenya where youth and women unemployment, um, hover in the 70% or greater range. So, Ken, while he had amazing grades coming out of high school, there weren't any jobs for, um, someone in his situation. Um, he didn't have a college degree and didn't have the right kind of network or access. He didn't come from sort of the right neighborhoods. So what happens often time, um, in these areas where there's a huge amount of unemployment is that people uh resort to the uh people resort to the, excuse me. One moment. Heather. OK. Sorry. All right. Sorry about that. So people resort to um the informal economy. So this picture right here uh specifically is uh a picture of what Ken used to do. Um He uh uh he was uh a producer of chang A which is a local moonshine which um believe it or not, if you can actually see this right here.

Uh This is actually a moonshine that is created with um with uh jet fuel. So, uh as you can imagine, this is a really challenging situation to be in. So where does our model come in? Uh We have a very purposeful hiring model at SOO. Um We believe that by giving people both training and a first job, this really helps them launch a permanent pathway out of poverty. So our only real criteria, it's not uh related to the education uh you know that you have or uh whether you have job experience. It's really whether you fall into the demographic that is living below the World Bank average po poverty line, we uh that is our recruitment base. Um Then what we do is we provide specific training in the um area of training, data and A I to um to this workforce, we employ them full time with benefits and living wages and from there. Uh and that work experience, it really develops into not just a transformation of having more income in your pocket, it really becomes a transformation of, of, you know, sort of not knowing what was ahead of you for the future to having a career path. Um It's an opportunity and environment to both develop skills, professionalism and be that first real entry into the workforce. Uh One of the things that we believe in deeply is measuring impact.

Um So we survey uh workers who leave Sasso and three years after employment, our workers are still on average, have an increase of four times their previous earnings. Uh We have a well over 80% success rate of people earning more than they did at soo after they leave or going back to university. So, you know, how does that really affect our, our work? Well, um as you can imagine, these are very um meaningful jobs. We have incredibly uh intelligent uh women and men who really lack that access to opportunity and when they are provided that they, they stay, um our retention rates are, are really industry leading with less than uh uh roughly 10% annualized nutrition. And what that means is that we have labeling experts. So I'm super proud of our teams who have done literally um hundreds of workflows and autonomous vehicles uh augmented in virtual reality. It's really quite incredible. And when it's combined um with our, with our technology platform, there's uh a pretty amazing solution that results in incredibly high quality training data. So high quality training data like why does quality really matter? Well, quality ultimately is is critical. Uh imagine a self driving car that can detect a motorcycle but not a bicycle or can read certain road signs but not others. So uh getting to that last mile of quality um is really important in the work that we do.

Um In addition to that, having a vertically integrated workforce allows our platform to get smarter and smarter. So the the platform really allows our humans, it's a machine learning assisted an. So it allows our humans to do what is uniquely human. And uh the more work we do on the platform, the smarter our systems get as we codify that knowledge of our workers. So um ultimately, um really data scientists and machine learning engineers who are looking to bring their models to market uh face training data challenges in really every aspect of their projects. It could be in R and D phase all the way to building um you know, building their models, uh like self-driving cars is a good example, all the way to um bringing those into production um and really being able to, you know, maintain the quality of their um their algorithms. So it's on the source. Um We really provide the full training data life cycle. Um Everything from uh basically identifying what are the gaps uh of the training data that you have. What should you be training on the actual uh preprocessing and transformation of that data, uh the labeling as well as quality assurance and, and finally, model validation.

Uh As you can imagine, if you are an organization like Walmart that has uh you know, the world's largest catalog of products, um those products are gonna change over time. So it's incredibly important that your product search algorithm stays as refreshed as possible so that um you know, consumers can continue to find your products. All right. So uh this is what it actually looks like. Uh This is a picture of our delivery center in Kampala, Uganda.

That's one of the areas we work in. Um So our workers come to a highly secure center. So, you know, bio biometric access and, and uh you know, leading technologies. And uh one thing that we're also very proud of is that uh we've built all of our facilities uh with sustainability in mind and have been uh approved for Corp Certification. So it's something that we're also uh pursuing uh ultimately, um it's really that combination of software and humans loop that really allows us to achieve um sort of true differentiators related to quality trust scale and of course, impact. Um We're very excited and super proud to say that we um we support 50% of the top 10 technology companies in the world uh at SOO. So um I wanted to share um some additional words about Lila Janna. Um she was our founder and uh very sadly, um she passed away just this last January. She was not just our, our founder and, and visionary. Um but uh she was a dear friend and she passed away from a very rare form of aggressive cancer. Uh She was, this is a, this is a conference about women in technology. And um she was a true woman in tech, a pioneering um social entrepreneur.

She had a very, very deep belief that this can be a force for social change and that we as technology leaders, one of the best, best and brightest out here. We really need to lead that charge and, and lead through action. We knew, you know, as, as partners, we knew we needed to create the very best software out there that our solutions could ultimately be not only delivered in uh you know, a very beneficial way for our clients, but ultimately, and most importantly, in an ethical way and an impactful way.

So our focus on on giving work as I shared a little bit more about the the mission of our business. It also has a very specific criteria. We hire 50% women. So, you know, absolutely, 100% of our focus from a recruitment standpoint is ensuring gender diversity. I'm extremely proud to say that this is not just at our agent and labeling level, it's all the way up through our management level um and up through the board. So we take a great deal of pride in having a diverse workforce and, and a very balanced workforce. Um Just a few uh personal notes. Uh Again, because this is a woman in technology uh conference. Um Is that, uh I, I thought I'd share a little bit that uh last year in 2019, we uh raised 14.14 $0.8 million in series A. Uh It's just a note that LA and I were quite a pair uh to minority women executives seeking funding for uh a software company. So that was really interesting. Uh We were oftentimes the only women in the room, but it was um really, really ultimately um something that was greatly beneficial because we ended up finding uh investors that, that not only, you know, really loved our product and felt strongly about um the promise of A I and had expertise in A I, but they also saw the value in our diversity.

So I just want to put it out there that, you know, people that, you know, there are, are people who value diversity and, uh, you know, I'm thrilled to be with, uh, the team that's supporting us right now. So I'll, I'll just, uh, maybe wrap with a couple, couple of things. Uh, one is that, uh, we've moved over 50,000 people out of poverty to date. Um, that is over, uh, 11,000 workers and all of their dependents. So that is our objective in paying living wages and benefits is to be able to support a family of four. And um you know, this is Martha. Uh I, I started uh this discussion with an example of Ken. This is Martha. She is an incredible young woman who joined us. She's um actually been out of s source for a few years now. She uh joined us after being unemployed for quite some time, unable to, to um get a job, not because of her talent, but because of, you know, her gender and where she was from and she joins SOO worked for us for a few years. Uh pretty much immediately after she joined. So she moved in out of um the slum area, she was living in, into formal housing, into an apartment. And last I saw her which was just a few months ago before all the lockdowns and COVID happened.

Uh I saw her in Nairobi and she is a leader in her online hospitality company. Um Just absolutely incredible what the power of work can do in terms of transformation and how technology plays an incredibly important role in making that happen. So, um I try to move a little bit faster there. I didn't give back all the time, Nicole, sorry. But uh thank you so much for uh for having me. That's my presentation.

No, this was really amazing, inspirational and um you know, that's a journey that you go on with someone and um I could tell that uh her work carries on through you and I'm sure um she would be very proud of all that you're doing for Samoa and for the world. These are inspirational stories. This is what it's about, this is what it's about to be women intact, to raise each other up to make the world a better place than we found it. And people are loving your presentation from all over the world wanting to connect again. I put her linkedin uh link in there. I'm gonna do that again right now so that you could stay connected. I assume that's best for you, Wendy.

Yeah, Lincoln is great. Thank you, Nicole.

Great. I just posted that just because I know you're in presentation mode. Uh I just wanna just give you a huge round of applause. Thank you for sharing this today. A little about your company and a little bit about your journey. People are saying it's very inspiring, they loved it. It's incredible. So if you loved it, you know, um follow her out on social and uh make ways to connect with her and to share the story and to share really the great mission of your company and focus on people. So thank you for doing that.