6.2023-London-Claira

KATIE HALL: Good afternoon. Thanks for having me. My name is Katie Hall. I am the founder and CEO of Claira and MIT MBA 2020. So I was finishing my MBA right is the world was ending, for all intents and purposes. The pandemic actually helped us launch. People started talking about all the mess in the labor market, the need to move supply quickly, keep up with demand.

So Andy Haldane actually in his keynote earlier perfectly cued up the radical experiment that we're doing here at Claira when he described the need to re-examine everything about the way that people learn, the way that we connect people to work. I think his words were malleable capabilities. So that'll be the context of my short talk today.

I'd like also for you to just imagine a world where the competencies of all humans and machines are in a global database updated in almost real time, plug in, plug out. Predictions can be made on what you'll need in a day, an hour, a week, a year. And also, you'll be able to be told what role a person should be in, what competencies they need to learn, what assets in your workforce you need to move around. That's the world we hope to contribute to.

So when customers, mostly industrial right now, come to us, these are the types of questions they're asking. Do people have invisible competencies in one part of the organization that I could use in another part of the organization? Do I have redundancies on humans and machines?

They are frustrated by job descriptions and resumes as a tool for management. Same with ATS systems. They want a more granular, equitable picture of what all people in their workforce can do. And Claira gives them that picture.

So we are a SaaS solution, machine-learning powered. We have two algorithm blocks that we built ourselves-- [? Coco ?] and [? Cody-- ?] and they track a database of 20,000 competencies-- globally applicable and cross-industry as well-- so that we can show companies real-time data on competencies individuals have, trends across teams, divisions, and things that they'll need to hire internally for, hire externally for, or project into the future for.

So problem and solution I just hit a little bit. Job description, resumes-- old, outdated. Include just under half the world's population. Not nimble enough. Not accurate enough, I believe, and hope that they are on the way out for good in place of the system that I described at the beginning-- a dynamic competency engine.

This is an actual use case. So as I mentioned, we're selling to mostly industrial companies right now. We have some mid-market and large industrials mostly in the US, but we are starting to get a lot of interest from Europe.

And actually, I worked internationally heavily in Europe for about 10 years learning about competencies and national qualifications frameworks, which you do very well here, and we do not do very well in the United States. So my work in Europe actually inspired Claira in part.

Ryan is a COO, mid-market industrial company, team of 1,000 multiple plants. He came to Claira because he hires a bunch of people, they go out into the plants, and he has no idea what their skills are, what their background is. He feels like that's costing him a lot of money, and it is.

So we try to onboard Ryan and the other customers very quickly. There's still trauma around the purchasing of SaaS. Is it going to take me a year to implement? How quickly am I going to see value as a company?

So we try to onboard with about five hours of Ryan's time invested on his part and value in four weeks. So ingest company data, onboard employees using a questionnaire to uncover invisible competencies. Once those two things come in, we use what we already have in our database of all the other users, and their dashboard is live. So value about four weeks later.

Ryan reported that he saved 500 hours of his own time in the first year, which is a lot if you do the math. And what is that worth-- a COO of an industrial company saving this much of his own time? He was trying to quantify skills in Excel when he approached us.

And you can also see very compelling employee utilization rates going up and retention rates also going up, which in industrials who can have up to 40% turnover, that's a big value prop.

The bolded quote in the middle came directly from Ryan. And I like to point this out because we are in a tough market right now in a lot of ways. And Ryan feels like this is giving him a competitive advantage against other industrials who either don't have any sort of competency tech in place, or are just using job description, resume-- sort of the old model, in his words.

These are the modules in the software. I won't spend a ton of time here. I'll be outside, and you can see these in the demo. But they basically give you visibility, uncover gaps and opportunities, engage-- so custom pathways for your employees based on their individual gaps not just generic training, and then marketplace, which allows you to hire internally and externally.

This is a quick screen grab of the most popular page in the app-- part of the employee onboard questionnaire-- where we can uncover invisible competences that they could contribute to the company, but that may not live on a job description or resume, especially if they have, as we heard about this morning, more of a nontraditional path into industry.

This is a snapshot of the dashboard. This is what admins get. This gets updated almost every 24 hours. Some modules updated every hour of competencies get added, they hire a new person, someone changes a role. And then a quick screengrab of how we process data.

So we do have two algorithm blocks that we built ourselves. We train on the large data sets, of course-- T5 GPT. And the intelligence is the data set that we own. That's of great interest to us. Our competency library doesn't exist anywhere else. It was built custom for Claira. And we're actually filing for IP protection on three components of the LLM [? reader. ?]

Quick traction slide-- we're actually at a million in revenue as of this week, which is very exciting. We raised about $3.5 million in venture funding, raising another round currently. And going from 10 now to 20 customers by the end of the year.

Seeking innovators across industrial-- industrial is very broad. We love advance manufacturing. Anybody who makes things is a great use case for us right now. And these are my other two co-founders who aren't here today. Love to come meet you outside. Thank you.