 Live from Orlando, Florida, it's theCUBE. Covering Grace Hopper's Celebration of Women in Computing, brought to you by SiliconANGLE Media. Welcome back to theCUBE's coverage of the Grace Hopper Conference here in Orlando, Florida. I'm your host, Rebecca Knight. We are joined by Elite Raz. She is the CEO of Junco, an AI-powered diversity and inclusion coach for companies. Thanks so much for joining us. Thank you for inviting me. So I'd love for you to just start talking about how you came up with the idea for Junco. Sure. So I grew up in Israel, originally from Israel. Spent about 40 years in the tech industry. Before that, doing computer science in high school, I was almost the only woman all along the way for like 15 years. And I think a weird thing, I never thought it's a weird thing. This is how I grew up. I was one out of two doing computer science in high school. Spent a few years in the intelligence unit, was the only woman around. And this is how I grew up. And then like two and a half years ago, I joined a group of women in product management in Israel. We like, I went to their first meetup. There was 250 women there. Israel people have this perception of everyone knows everyone. And I went into the room and I literally know, like, new, new one. And I'm like, that's weird. And then I think I realized like we have a problem. I went back to two other friends. We worked at another venture before. Said, hey, what do you think about changing what we're doing to like doing something for women in the workplace? And I'm like, actually, that sounds awesome. And we started thinking about like, what is already outside in the market? What are company is doing now? And I come from a lot of cybersecurity background. And like, what do you think about doing anti-virus for biases? And this is how we started this AI stuff and everything like this. And as we move forward and started to talk with a lot of companies, we realized the biggest barrier for companies is like, understand what's happening on day to day stuff for employees all around the world. Like if they're head of HR or head of diversity sitting in San Francisco or whatever in their headquarters, how do you know what's happening with your employees? Like in a really low level, in offices around the world. And we realized like- So it's not just for the recruitment. It's also in terms of who's getting promotions, who's getting the choice assignments. That's right. What kind of language are you using when you talk on Slack? What type of code review do you give to a female engineer versus a male engineer? Who gets promoted? What type of language do you use on peer-to-peer valuations and all these types of stuff? That stuff is so hard and it sort of seems, the code review assignments, it seems like a minor thing, but in fact- It's really important. Like if you get like, you need to fix this at cash mark, you're like, that's not really nice. And it doesn't make you feel like, okay, I want to go ahead and fix it. And probably you don't give this same thing to a male developer. Like maybe there's another way to do it and you use different phrases and different tone. And also we see like on Slack messages when there is a development channel, usually you're not going to see women and people of color are as active as men, just because they're usually a small portion of the team, even one person of the team. So I think this is like the main stuff that's happening on day-to-day stuff that are not like, do I get the most important role in the company? But actually, do I get a spot? Generally speaking in the company, do I feel comfortable? Like if someone making a joke is like, you look so gay as a joke, and you as a gay person, whether you're outspoken gay or not, like publicly spoken about it or not, then don't feel very comfortable, even if it's a joke. It's not really funny. Right, right, right. So how does your technology work? So it detects these biases. It understands when there is aggressive or hostile language to women or other minority groups. And then what? So basically we connect to these everyday SaaS platforms companies are using. So you mentioned recruiting is one of them, Slack, Salesforce, basically all the companies around here. Then once we connect to these platforms, we fill out the data in real time all the time. We analyze the data, we look for patterns, and then when we get this metric, okay, there is a pattern here that is probably based on biases. We reach out to the most relevant person, like the person who has the most effect on the current situation. Whether it's you as a female developer that needs to be more active, or you as a recruiter that was just skipping these 10 diverse candidate CV reviews. You as an individual can make the most impact on the current situation. We're going to reach out to you, whether via email or Slack message, and say, hey, this is the situation, and here is how you can fix it. So we have another engine that match a problem with a solution. With an action. Yeah, with an action that you can do in less than two minutes, it should be like a really quick thing. You can do on the go, you don't need to, okay, I need to set time for this juke thing, you know, a super quick thing. Right, right. You can do what you need to do, and it basically should help you either really improve the situation or basically overcome it before it gets to like, what we call it like micro events of unconscious persons, before it gets like really big thing. So are people, so it really is putting the onus on the individual to act, and do people do it? Is there follow through? What are you seeing? I think that the numbers that we have on even open rates for the insights that we send and follow-up rates, I think every marketing company in the US would love to have these numbers, like they are really, really high. I think just people, like for the first two times, they give it a try, and when they see that it's really helping, they just keep doing it. Like we have one company that reach out to us and say, we know you have a limit of like three engagements a week because you don't want to bother us. Can you take it off? We want to get all of them. Like we really find them helpful on our day-to-day stuff. Can you give us, like can you give us more of these insights? So I think people are like really into giving it a try, and then see that it's helpful and keep using it. Like we really see high improvements, so I think that's another good reason for people to kind of like keep engaging. So yeah, people are super happy about it. So what are you finding? What do your clients tell you is the return on investment here? I think the first main stuff that we see one, because we have a lot of capabilities of like, let's say recruiting for example, when you look at a recruiting and a company say, like we want to improve our recruiting numbers, they don't really know beside the fact that someone voluntarily gives their like ethnicity, age, gender, whatever, they don't know who is the applicant, unless they manually tag like one person by one. We know how to analyze gender and race automatically by email addresses for like 90% of the candidates. So it actually gives a really clear picture for a company like okay, what is happening in our recruiting efforts and where are like the pitfalls and where do we fail? And it's basically like turning the light in a place they had no clue what's going on. Showing them their blind spots. They had no idea what's going on. And other places like what's going on on Slack channels, I don't think anyone here knows what's happening on those Slack channels. It's really, really hard to follow. So I think it's the small spots and they're like little places that we can like basically turn on the lights for a lot of companies. And so who are your companies? Are they already the forward thinking companies or are you seeing? I think at this point you have to be a forward thinking company to go ahead, give a third party access to all this stuff. Really want to make a change. Honestly I think you need to be like a few hundreds, maybe lower a few thousands to actually being able to make a quick change. Like for our companies that have a few hundred employees, they see in less than three months like five to eight percent improvements on your recruiting efforts, like actually hiring more diverse candidates. I think when you get to a size of like 100,000, 200,000 employees, making a one percent change. It's a lot harder. It's not hard. So what is your message to those companies? Wow, I think A, start with business units. Don't make this huge announcement that you're going to be 50, 50 by 2020. To get to 50, 50 by 2020, you need to fire half of your team and then hire half diverse candidates. So start small, start small. Start small, start where your pains are really are. Don't say you have 50, 50 when all the 50 are in marketing and sales and like assistance or whatever. And then on your R&D teams, you have like 10, 90, which is most companies have. So start small and I guess lead by example by putting money into internal work and not marketing out hope. Like go ahead and do like volunteer work, come here to Grace Hopper. This is nice, but this is more customer facing marketing versus actually doing something internally to change the numbers. Great, great. Well, Elite Roz, thank you so much for joining us. It was a pleasure. Thank you very much. We will have more from the cubes coverage of the Grace Hopper conference in a little bit.