6.15.23-STEX-CA-Intro-Claira

ARIADNA RODENSTEIN: So we've arrived at the startup lightning talks. And I think we're going to bring some chairs for the Q&A session as well and an extra mic for the startups. But I can get-- start it in a second. In any case, I'll just give you a little background. So this is a more fast-paced part of the program. So we're going to change the speed a little bit.

I'm, Ariadna Rodenstein, Program Manager with MIT Startup Exchange. And on behalf of my colleagues, we're very excited that you're here joining us in person and also via the Livestream. I will give a brief overview of Startup Exchange and then we will hear from the startups. We have 10 exciting startups with very diverse technologies, with a variety of applications. So I'm looking forward to having the engagement happen between the corporates and the startups.

And just a little background on demo day. This is the first time that we're hosting it live and we're excited to be here in California. We usually host demo days virtually on a quarterly basis and we'll continue to do that. So I hope you join us for that. The next one will be in September.

But we thought it would be great to be here in person and add a bigger agenda. And so we're thankful to all the speakers as well besides the startups. And the objective of demo day is to present startups to you that are more recent additions to Startup Exchange so that you can meet them earlier rather than later for potential for collaboration.

So MIT Startup Exchange was created over seven years ago within the Office of MIT Corporate Relations. And as you heard earlier, this is also home of the industrialism program or ILP. And our mission is to foster collaborations between MIT connected startups and ILP members. The startups can be based on MIT licensed technology or also be founded by MIT faculty, staff, or alumni. And they can also be vetted by some of our MIT partners, including the engines, CSAIL, MIT.nano, et cetera. You might have heard of some of them as well.

And we have over 1,000 startups in our program and they usually come to us at the pilot stage or beyond and they cover many sectors and many geographies. And you might have heard of Stacks 25. That is a program within Startup Exchange where we provide customized support to 25 startups over a period of 12 months. And they get referred to us by our MIT peers and then we lead the selection process.

And so how can you engage with these startups being an ILP member? One way is to join us at events like today's and we also have a lot of opportunities in other conferences that we host throughout the US, Latin America, Asia, and Europe. And the benefit for ILP members is that we can plan and tailor a program according to your needs. And the benefit for the startups is that we take them to these markets where they are expanding into or have a presence on their growing.

And as an ILP member, you also have access to opportunities. These are challenges where you can post one in our website, use that platform, and start up supply. And then you can select them. And where there's a good fit, they can work with you to help you solve a problem, a specific problem that you may be facing in your industry. So I hope that you're taking advantage of these benefits and let us know any questions also throughout the day today.

And we also like to share some of the success stories. These are some of the ones that have been made public over the past few years. And they take different forms. It could be that a corporate does a pilot with a startup or they become a customer. There's R&D partnerships. And also all the way to an acquisition, of course. And so I hope that some of the conversations and introductions that happen today will lead to more of the success cases.

And before I turn it over to the first startup, we still have a couple of events coming up this summer. Next week will be in London for a Work of the Future Symposium and then we'll be headed to Australia for Energy and Mining. So please check out the ILP and Startup Exchange websites. You can register for this and join us. And the same for the fall, we're going to have a very exciting and robust schedule for the fall. We'll be posting those so please check that out.

And so these are the 10 startups today. We're going to have two sessions this morning. We're going to start with the first five and then we're going to do Q&A. So a reminder to just use as well Pigeonhole to post your questions. Just at the beginning say which startup it's for or if it's for all of them. And we'll get started. Thank you.

Well, we're going to start with Claira, which is workforce optimization for the work of the future and I'd say the future is now. There's no stairs on this side.

KATIE HALL: OK. All right. Good morning. Thanks for having me. Glad to be here.

My name is Katie Hall. I'm the founder and CEO of Claira. And I was an MIT Sloan MBA 2020. So I'm going to blow your minds right off the bat today and challenge you to think about your workforce as not just people, but all the machines that are also part of your work force. Software, hardware, human intelligence, machine intelligence. This is how we have to manage our workforce now going forward.

So when customers come to us, these are the types of questions they're trying to get answers to. Do people have invisible skills that I could operationalize somewhere else in the company? Are there skills that people have from being a veteran, an immigrant, an Uber driver, things that are invisible not on a resume, not on a job description? Same questions for their machine assets.

Claira knows all of these things. We are a global competency warehouse. Our goal is to be the infrastructure for the future of work. Everything that everybody can do everywhere in the world updated almost in real time. It's sort of unbelievable to me that we don't already have this, that we're still using job descriptions and resumes. We are subscription software powered by AI and we have a database of 20,000 competencies in the back end that cover both human and machine talent. This is a snapshot of the dashboard that companies get so that they can start to understand their workforce better in a more dynamic way going forward.

So job descriptions, resumes, in my opinion and in many other people's opinions, are on the way out permanently. Hopefully by 2026, 2027. Too slow, too biased, not granular enough. Humans-- only half of humans have an actual resume, have a college degree. We still have to uncover what all those humans can do. Machines obviously don't have a resume or a college degree so we need a new model.

Companies who come to us are trying to look for what the new model is. We believe it's just this granular data set of competencies. We work with a lot of industrials right now, that's our main segment and that's by design. Industrials are already sharing work with machines and so it's a very easy step for them to figure out how to integrate humans and machines as part of their workforce planning.

Ryan is an actual customer of ours, chief operating officer who came to us because he said, "I hire a bunch of people and they go out into the plants and I have no idea what they can do or the skills they're using every day. And I know that's costing me a lot of money. And it's also not helping me plan for my big goals for 2030." We intentionally built the software to be incredibly quick and light to onboard. Value in four weeks.

So we meet with the customer, we figure out what their goals are, we ingest their data, and four weeks later they have a dashboard that starts getting updated for them. The machine learning starts giving them recommendations about actions they should take to optimize their workforce. And they go from there. So our goal is to be very quick and light, onboard really easily. So that as we've been talking about this morning, companies can do experiments for low risk on their end.

About $100,000 annual subscription against the size of the problem we're finding that this certainly isn't a barrier, especially depending on company size. Ryan reported that he saved about 500 hours of his own time the first year that he had Claira. Time he wasn't spending trying to catalog skills in Excel, for example. And that he saved about 1.7 in reported human capital costs to his organization. So less turnover retentions going up, utilization of employees and machines is going up. So he was able to tie dollars saved to that.

This is a quote that was in a press release recently in the center that's bold. This is a tough market. This, right now, it's tough to be a startup right now. And Ryan mentioned that he feels like he has a competitive edge because he's headed toward the future and using the new, faster system against his peers who are still using the old way.

There are a variety of modules within the software, of course, like all good subscription software. You can choose all of these or one or two or three. Uncover all the things your people and machines can do, highlight the invisible talent that you're not taking advantage of right now, engage your employees so that they keep updating their data, they get upskilling opportunities that are customized to their gaps, and then marketplace allows you to fill needs internally before looking externally. So lots of big companies are thinking about internal marketplace.

This is one of the most popular screens in the whole app. This is one of the invisible value questions that the employees actually fill out. We choose competencies for them based on these answers and we uncover things that the company didn't know about them and can then use after that. Here's a screen grab of the whole dashboard once your whole workforce comes, in human and machine. This gets updated in almost real time and allows the company to run the business based on that.

We have our own large language model that we built three years ago trained on all the big data sets, of course. This is a perfect use case for machine learning. Once it starts identifying patterns about what people are good at, machines are good at, it can start giving you actions that you should take. Some quick correct metrics. And then I'll pause, end on this slide.

We'd love to talk to industrials. Lots of you are here in the room today about what you need and potential to partner. Thank you.

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