Astra Wellbeing

0:01 here, Richard here at Bedmore Technologies, and I want to talk about the solution that we were able to build for Asher Wellbeing.
0:07 So, just some context. Um, Asher has had, uh, a whole bunch of initial success, um, they're a funded startup, um, they're currently attacking the market, um, and, uh, you know, we're very excited to see where they take this, this product, uh, into the, into the future, but just some context about what
0:25 they do, um, so they have a solution that's SMS-based that is meant to reduce burnout in healthcare. Organizations. Reduce Workforce Burnout in Healthcare Organizations. So, specifically, um, this is supposed to provide, um, a method to provide your co-workers with recognition to allow, um, you know,
0:47 people that are being attended to at these healthcare organizations the opportunity to provide people, um, in the workforce that are attending to them with messages of recognition.
0:56 Or encouragement, or motivation, um, and also provide that, like I mentioned earlier, from a peer-to-peer standpoint in the workforce, you can send, um, your co-workers messages of encouragement, recognition, and then every morning, as well, you get a message of, of motivation.
1:11 This whole, um, ecosystem is built just to reduce, uh, burnout and to keep people motivated, uh, fulfilled, encouraged, ready recognized in their, you know, day-to-day activities.
1:23 So, how this works from a high-level perspective is essentially, um, Asher meets with an organization, they integrate with the HR system, um, to upload all of the employee, um, profiles, phone numbers, et cetera, onto their platform.
1:39 Once employees are on-boarded, they get an introduction text saying, hey, by the way, your organization has signed up to Asher Wellbeing, here's your dashboard, and here's how you can send messages of recognition to your co-workers.
1:50 Now, there's some very, very interesting, um, methodology here. So, first and foremost, um, we built this platform to be SMS-based.
1:59 So, specifically, in high-octane environments, you don't want to be opening up another app. I think the notification, like, If you're getting in-app notifications.
2:08 That someone sent you a message of recognition, you get a ton of in-app notifications already from other platforms all the time.
2:15 But you don't get many text messages. I think the open rate on text messages is over 90%. So, we wanted it to be as seamless as possible.
2:23 So, you're just getting text, right? You can opt out, of course, of these texts at any time from your dashboard.
2:28 But, regardless, like, we want a high-visibility way, so you can, you can get the recognition in a high-octane environment. So, it's SMS-based.
2:37 It's not an application. It's driven through SMS and through the web. Uh, so, you can click a link that an SMS message sends to you.
2:44 You can see your dashboard on your custom link and then send messages to co-workers on that link as well. Very streamlined, very seamless, meant to be as adaptable as possible.
2:55 The next thing that was interesting, We'll see you was this integrations with systems, right? So, when you're dealing with large organizations, right, like they don't necessarily have a CSV of, you know, everyone that they can just, it's different per org.
3:09 What HR platform they're going to be using is different. There's a level of setup that's needed. So, building that to be as seamless as possible, uh, managing that sort of, uh, call it an integration, but basically, you know, all org onboarding has been very interesting to manage.
3:23 The training associated with that as well. Just planning out a road map to how best to attack that at larger organizations has been very interesting to plan out as well.
3:32 Next thing that's been interesting, I'm going over here, is the monitoring and quality, right? So, um, again, as mentioned, basically how it works is you get a text message once your organization signs up.
3:42 You get a dashboard where you can search for your code. Um, basically co-workers by name, and then send them, you know, messages of recognition.
3:51 This also reduces and protects privacy because phone numbers are not exposed here. Uh, you're only able to send messages within this ecosystem of being able to search up co-workers by name, right?
4:02 So, it's not exposing, especially in a large organization, you don't want, like, phone numbers just getting, you know, there's the potential that you don't want phone numbers getting shared around.
4:11 I know some organizations do, but, um, there's the potential, you know, that you can mitigate that and just have it all go through the platform.
4:17 Um, that being said, you want these, especially, you have the ability to send custom messages of recognition. Now, there's templates and default messages of encouragement and recognition that you can send to your co-workers, but, you know, there's also custom ones that you can send.
4:31 So, this is where monitoring and quality comes in. So, you don't want people having conversations on the app. You don't want flavored messages getting sent back and forth between the app.
4:41 So, there's a level of monitoring and quality. So, we built the system to help, you know, the actual well-being team manage the, basically, the quality of content, make sure that every message that is getting sent back and forth through the platform is appropriate.
4:53 It's not talking about plans after work. It's not talking about, you know, uhm, inappropriate content. It's just specifically talking about messages of encouragement and recognition.
5:04 Uh, so, we built a system so the Astra well-being team can approve that and monitor that quality if needed. Now, what's really cool is this is, I think, where a very cool use case of AI came in, is you can have a decent amount of that legwork done by AI, uhm, basically, monitoring.
5:21 So, you can have AI basically read the messages that are getting sent in the platform, determine if they're appropriate, and if it's not confident in its decision, then that gets escalated to, uhm, an actual, you know, like a person where they can manually audit it.
5:35 But, regardless, like AI, this is a very, very cool use case of AI, very niche use case of AI, but content moderation, uhm, that specific feature is has been implemented into this application, I think is very cool.
5:48 The last really cool AI feature is the translations. So, uhm, you know, you have the ability on the application to set your language preferences.
5:57 Uhm, if you want to receive your messages in a certain language, especially if it's an international organization or something like that, right, uhm, you have the ability where AI will auto-translate those messages of recognition and encouragement to your preferred language.
6:12 Again, just a really, really cool use case of AI in this specific application. Regardless, this SMS-focused platform, the fact that it, uhm, you know, we have systems and processes built to integrate with HR systems, uhm, the fact that it's able to, it has systems for monitoring and quality of messages
6:31 , and we have some really, really cool niche AI features that, again, the user will never see, but definitely have business use cases, uhm, create this ecosystem of optimized recognition, a seamless, adaptable way for optimized recognition.
6:45 And like I said, this is a really, really cool project to work on, a lot of ideation, a lot of brainstorming for adaptability, uhm, had a great experience working with the actual OB team.
6:54 I want to specifically shout out Martin's on the team who's helped bring this all project to life, uhm, and is currently maintaining the project, and we, you know, we wish the actual OB team a ton of success as they basically bring this to market, uhm, and start getting some traction here, so.