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Smarter Cameras Are Changing Logistics Safety Norms · Speaking of Supply Chain

• 0:00
  Speaker 1: Generally speaking, a efficient facility as a safe facility and
• 0:03
  Speaker 1: vice versa. So as we work with customers, a lot
• 0:05
  Speaker 1: of the use cases that we support sort of bridge
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  Speaker 1: the gas between efficient operations and making sure that they
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  Speaker 1: have a safe work department.
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  Speaker 2: Hello and welcome to speaking of supply chain, where we
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  Speaker 2: explore trends, current events, and innovations impacting the logistics and
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  Speaker 2: supply chain industries. I'm your host, Ellen Wood. Large machinery,
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  Speaker 2: heavy lifting, and high traffic are inherent risks in warehousing
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  Speaker 2: and logistics, and ensuring employees safety is critical. Companies that
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  Speaker 2: proactively invest in robust workplace safety programs not only protect
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  Speaker 2: their workforce, but also enhance productivity, reduce operational disruptions, and
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  Speaker 2: foster a culture of trust and engagement. Joining me for
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  Speaker 2: today's discussion is Jack Brannef from VAUXHALLAI.
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  Speaker 1: Welcome Jack, Thanks Allen, great to be here.
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  Speaker 2: Great to have you. So tell our listeners a little
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  Speaker 2: bit about what VAUXHALAI is and how it works.
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  Speaker 1: Vauxhall is found in twenty twenty in San Francisco with
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  Speaker 1: the mission to protect people who make the world essentially work.
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  Speaker 1: So we are a computer vision AI company that leverages
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  Speaker 1: existing security camera infrastructure and relays it with our AI
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  Speaker 1: and computer vision models to essentially flag risk in real
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  Speaker 1: time and allow our customers to be a lot more
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  Speaker 1: proactive as they're mitigating risk and driving safety culture within
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  Speaker 1: their facilities.
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  Speaker 2: So you said twenty twenty, and the question begs, was
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  Speaker 2: it a reaction to what was happening in twenty twenty
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  Speaker 2: and slightly before that, or did you was this already
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  Speaker 2: in the works as just part of the logistics industry.
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  Speaker 1: So I actually love our origin story. So our founders
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  Speaker 1: are some very impressive people, espe on the technical side.
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  Speaker 1: They didn't necessarily go into it thinking that they were
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  Speaker 1: building technology for the purpose of workplace safety. They were
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  Speaker 1: more than anything, taking some of their experience, you know,
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  Speaker 1: working at places and institutions like Carnegie, Mellon, Google, Uber,
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  Speaker 1: a few of them coming together sort of playing with
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  Speaker 1: really innovative, breaking edge tech at this time when everyone
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  Speaker 1: had a little bit more time on their hands or
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  Speaker 1: figure it out and realize that there was really a
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  Speaker 1: lot of opportunity in the computer vision space. And you know,
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  Speaker 1: ultimately we're able to work with some advisors and for
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  Speaker 1: a few of our funders pull on some really personal
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  Speaker 1: stories and find a neat way to take this innovative
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  Speaker 1: tech and tie it to an area of opportunity that
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  Speaker 1: you know, both allows us to build AI with a
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  Speaker 1: really positive mission, which ultimately is to ensure that people
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  Speaker 1: get home and return safely to their families each night.
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  Speaker 1: There's also a massive market opportunity. So I think as
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  Speaker 1: they were getting in and realizing that the type of
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  Speaker 1: product fit and the existing infrastructure that really was in
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  Speaker 1: place in a lot of these facilities, you know, there's
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  Speaker 1: over one hundred and sixty seven billion dollars in injury
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  Speaker 1: related claims each year, and so thinking about the market
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  Speaker 1: opportunity there, purely from a business standpoint, there was there
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  Speaker 1: was a lot of run. But again I think that
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  Speaker 1: the initial reason for making the correlation was a lot
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  Speaker 1: more on sort of the much more personal side of
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  Speaker 1: what we're doing, which again is ensuring that folks that
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  Speaker 1: really drive our economy, drive our country, you know, are
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  Speaker 1: they are able to work on or return safely to
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  Speaker 1: their homes each night.
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  Speaker 2: That's amazing. Now I've interviewed others in this same general
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  Speaker 2: field of you know, workplace safety, and you know the
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  Speaker 2: types of it's usually a wearable tech that allows to
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  Speaker 2: collect those biometric markers and understand what's happening as people
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  Speaker 2: are moving physically within their job and their function. So
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  Speaker 2: you said yours integrates with the existing security systems. So
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  Speaker 2: the security cameras and just watching an overview, how does
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  Speaker 2: that work exactly with the overlay? Is it just identifying
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  Speaker 2: movement patterns? I mean, is it able to get close
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  Speaker 2: enough and granular enough to see some of the smaller
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  Speaker 2: tasks that are happening, especially when we're talking about a
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  Speaker 2: security system, because I don't know, I've seen some security
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  Speaker 2: system video and it's not always the best quality, So
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  Speaker 2: I'm interested to understand a bit more of.
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  Speaker 1: How that works. Yeah. So, I think first major observation
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  Speaker 1: from our end is the vast majority of facilities that
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  Speaker 1: we work with, whether it's a manufacturing site, you know,
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  Speaker 1: a e commerce or retail facility, a logistics hub like
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  Speaker 1: a quarter, or a terminal, they really do have a
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  Speaker 1: lot of the camera infrastructure in place. And really, even
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  Speaker 1: over the last few years, we've seen more and more
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  Speaker 1: companies you invest in having sort of robust cameras that
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  Speaker 1: really cover a vast majority of the areas that we
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  Speaker 1: want to see. There's certainly you know instances where we
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  Speaker 1: work with customers to optimize the camera views, to maybe
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  Speaker 1: move them around, add a couple cameras, to really focus
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  Speaker 1: in on some of the use cases that are going
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  Speaker 1: to drive value. But honestly, I would say that sort
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  Speaker 1: of a minority at this point. I'm at least from
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  Speaker 1: my seat, my perspective, you know, a lot of the
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  Speaker 1: warehouse or again these different these different sites that I'll
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  Speaker 1: go visit when we're seeing our customers have the infrastructure
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  Speaker 1: in place. In terms of actually deploying our software, our technology,
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  Speaker 1: it's it's really quite seamless. There's a small hardware component
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  Speaker 1: we do ship a box out to the sites that
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  Speaker 1: compress the videos and make sure we're not putting any
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  Speaker 1: strain on their network infrastructure. But generally speaking, you know,
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  Speaker 1: we can be live with our customers in a matter
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  Speaker 1: of days, given the way we're able to again deploy
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  Speaker 1: on top of the cameras that they have in place,
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  Speaker 1: and in some cases, you know, a week from working
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  Speaker 1: with the customer initially, we're already at a point where
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  Speaker 1: we're looking at live data from their facility that has
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  Speaker 1: been you know, essentially run through our models and we're
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  Speaker 1: we're flagging that risk and having starting to have those
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  Speaker 1: conversations around how do we use this to actually drive
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  Speaker 1: impact drive change management with our customers sort of in
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  Speaker 1: that timeframe, which is pretty awesome and sort of a
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  Speaker 1: different experience for me coming from a lot more enterprise
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  Speaker 1: technology that may take weeks to months at deploy. Being
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  Speaker 1: able to see this sort of almost in real time time,
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  Speaker 1: you know, drive action for our customers is pretty remarkable.
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  Speaker 2: Yeah, that is a really quick turnaround time. So what
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  Speaker 2: types of things is the software designed to capture and
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  Speaker 2: collect and study in terms of you know, workplace safety, ergonomics,
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  Speaker 2: and movement.
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  Speaker 1: Yeah, so really, you know, the use cases we support
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  Speaker 1: really align or generally aligned to sort of the largest
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  Speaker 1: leading indicators of injuries and so, you know, just to
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  Speaker 1: give a handful of examples, you know, a large focus
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  Speaker 1: on ergonomics, so overreaching bending, you know, are we seeing
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  Speaker 1: are we seeing movements that essentially you know, could lead to,
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  Speaker 1: especially if repeated over and over, pretty serious injuries. A
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  Speaker 1: strong focus on vehicles, so you know, proximity vehicle to vehicle,
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  Speaker 1: vehicle to pedestrian speeding. Speeding has been a really interesting
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  Speaker 1: use case that we've been working with a lot of
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  Speaker 1: our logistics customers on even some outdoor views looking at
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  Speaker 1: semis sort of ripping through facilities. And then another general
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  Speaker 1: category of large categories area controls. You know, as a
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  Speaker 1: person somewhere that they're not supposed to be, is an
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  Speaker 1: object sitting somewhere that it's not supposed to be blocking
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  Speaker 1: an exit blocking a fire extinguisher is a is a
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  Speaker 1: door left open for too long, which you know, in
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  Speaker 1: some cases if you're in a cold storage facility, could
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  Speaker 1: be a big issue from you know, from an energy
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  Speaker 1: efficiency standpoint. So you know, we're very focused on safety,
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  Speaker 1: and you know, a lot of it's the LEA again
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  Speaker 1: the leading indicators that ultimately could lead to individuals getting injured.
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  Speaker 1: But there's a really interesting sort of operational component too
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  Speaker 1: as you're thinking about you know, some of the things
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  Speaker 1: I different I mentioned, you know, generally speaking, a efficient
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  Speaker 1: facility as a safe facility and vice versa. So as
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  Speaker 1: we as we work with customers, a lot of the
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  Speaker 1: use cases that we support sort of bridge the gas
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  Speaker 1: between efficient operations and making sure that they have a
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  Speaker 1: safe work environment.
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  Speaker 2: So I'm interested in some of the tangible benefits, especially
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  Speaker 2: in this case since we're using a structure and an
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  Speaker 2: infrastructure that the company already had, which is security cameras.
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  Speaker 2: We're assuming that they have them and they're going to
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  Speaker 2: be pointed at the right things. So, you know, if
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  Speaker 2: a company already has a security camera focused on these
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  Speaker 2: logistic areas, you know they should be able to see
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  Speaker 2: using this footage, if if someone's speeding through the area,
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  Speaker 2: if someone's wearing their ppe, if someone is you know,
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  Speaker 2: not stacking things the way they're supposed to, or if they're
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  Speaker 2: bending too often. But obviously the AI helps identify those
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  Speaker 2: things and those patterns a little bit more quickly. So
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  Speaker 2: what are some of the tangible results that your clients
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  Speaker 2: are able to receive in these these benefits? What are
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  Speaker 2: they able to find more easily and what are they
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  Speaker 2: able to correct more quickly?
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  Speaker 1: I love this question. This is this is really sort
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  Speaker 1: of where my role in my team focuses with our customers.
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  Speaker 1: How do we ensure that we are driving tangible benefit,
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  Speaker 1: you know, while at the same time, you know, a
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  Speaker 1: lot of times sort of driving more of the qualitative
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  Speaker 1: benefit of uh, you know, our customers feeling like they
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  Speaker 1: are they're having a much safer facility, But tangible benefit
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  Speaker 1: is critical to ensure that you know, customers want to
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  Speaker 1: continue working with us, that we're able to expand, and
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  Speaker 1: that frankly, we know that we're being successful. And so
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  Speaker 1: first starting with maybe sort of the tackle morgnity gritty
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  Speaker 1: in terms of how we measure it. You know, one
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  Speaker 1: of the one of the primary ways is looking at
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  Speaker 1: claims information, and so you know, as we work into
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  Speaker 1: a facility, maybe running three years of their historical data
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  Speaker 1: where injuries occurring, you know, what area of the facility,
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  Speaker 1: what type of actions are actually driving injuries they're driving
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  Speaker 1: sort of lost time, you know, things that you know,
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  Speaker 1: both impact operations, but also you know, again to sort
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  Speaker 1: of our mission, you are leading to unsafe environments, and
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  Speaker 1: so we'll use that data to really drive focus. And
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  Speaker 1: it definitely changes from site to site. You know, working
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  Speaker 1: with a customer pretty pretty heavily. Right now that's very
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  Speaker 1: focused on you know, ergonomics from a very sort of
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  Speaker 1: manual packing and unpacking processes, and so they're using our data,
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  Speaker 1: you know, around understanding exactly where in the facility they're
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  Speaker 1: getting the most ergo hits, sort of the time, what
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  Speaker 1: shifts it's happening. They're running heat maps, so able to
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  Speaker 1: sort of see exactly where in a camera view these
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  Speaker 1: actions are occurring and then using that to drive sort
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  Speaker 1: of better coaching. You know, how do they build a
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  Speaker 1: much sort of more robust safety program to actually coach
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  Speaker 1: to the behaviors that are occurring and be very targeted.
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  Speaker 1: But I think very you know, in terms of extremely
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  Speaker 1: tangible changes that they're able to make without driving, you know,
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  Speaker 1: complete change in human behavior. They able to invest in
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  Speaker 1: the infrastructure that makes the job a lot more efficient,
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  Speaker 1: so you know, new tables, changing sort of the configuration
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  Speaker 1: of conveyor lines and belts and the heights at which
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  Speaker 1: so you know, those risky behaviors aren't happening in the
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  Speaker 1: first place. So I guess sort of in summary, you know,
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  Speaker 1: regardless of its ergo vehicle, you know, area controls, you know,
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  Speaker 1: compliance with certain article closing like bump caps or safety vests.
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  Speaker 1: You know, we really see two core ways of tackling it.
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  Speaker 1: You know, using the information to drive a lot more
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  Speaker 1: efficient management of processes and safety based programs, but then
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  Speaker 1: also our customers taking a lot more initiative of how
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  Speaker 1: do we use sort of a data first approach to
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  Speaker 1: configuring our facilities to really optimize for a much safer
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  Speaker 1: work environment.
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  Speaker 2: And you've mentioned a couple of different aspects of what
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  Speaker 2: you're able to measure, to record and measure, and we're
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  Speaker 2: talking about logistics in general. You mentioned, you know, ports
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  Speaker 2: and logistics facilities three pls is what comes to my mind,
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  Speaker 2: you know, doing logistics from multiple different brands manufacturing, how
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  Speaker 2: does the platform adapt to the unique challenges of those
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  Speaker 2: because those are not exactly interchangeable. There's distinct differences between
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  Speaker 2: those types of facilities and the work that's done within them.
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  Speaker 1: A couple lots here. First and foremost, our platform is
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  Speaker 1: quite flexible and our models are quite flexible, especially the
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  Speaker 1: use cases that we've really decided to sort of prioritize
• 12:09
  Speaker 1: in terms of the offerings we provide to our entire
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  Speaker 1: customer base, regardless if it's a if it's a terminal
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  Speaker 1: or inside a warehouse or within a back of a store.
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  Speaker 1: You know, a lot of times those same sort of
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  Speaker 1: behaviors around organomic risk vehicles moving around, they exist sort
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  Speaker 1: of across these different facilities. So, first and foremost, the
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  Speaker 1: platform is quite flexible in that regard. But I think
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  Speaker 1: one thing that's really unique about our approach in terms
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  Speaker 1: of how we developed our software and our AI is
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  Speaker 1: we're constantly training based off of site level data and
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  Speaker 1: then you know, essentially optimizing our models based off the
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  Speaker 1: insights that we're seeing customer by customer, site by site,
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  Speaker 1: use gates by use case, and so you know, how
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  Speaker 1: do we make sure that you know, we are capturing
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  Speaker 1: you know, vehicle proximity when it's a tugger versus you know,
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  Speaker 1: a forklift. You know, it's constantly sort of taking those
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  Speaker 1: those data streams from different sites in and making sure
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  Speaker 1: that you know, those use cases are are tangible and
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  Speaker 1: work for the individual operations that you know, slightly differ
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  Speaker 1: between the different types of customers that we support.
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  Speaker 2: Interesting and one other thing that comes to mind right now,
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  Speaker 2: and it's it's unique because we're in this age where
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  Speaker 2: we're seeing a lot of autonomous vehicles and those interacting
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  Speaker 2: with human lines of transport within these facilities. How does
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  Speaker 2: that factor in when you're when you're dealing with I mean, obviously,
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  Speaker 2: this this autonomous vehicle is following a track, it's following
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  Speaker 2: a path that it has been programmed to do. But
• 13:46
  Speaker 2: then you're having to deal with the human element of
• 13:48
  Speaker 2: don't walk in front of the train as it's coming
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  Speaker 2: at you, or it's going to cause a disruption or
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  Speaker 2: potentially cause an injury. So how does that factor into
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  Speaker 2: what you're able to measure or does it even.
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  Speaker 1: Make a difference. Well, I think it's I think it's
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  Speaker 1: a really interesting point and I think we're you know,
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  Speaker 1: it's an extremely exciting time just for this our industry
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  Speaker 1: in general, and I think, you know, particularly computer vision
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  Speaker 1: and what we're doing, we're going to continue to see
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  Speaker 1: so much sort of rapid iteration as AI continues to
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  Speaker 1: drive you know, sort of more and more workflow within
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  Speaker 1: industrial facilities. That being said, you know, we have strong
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  Speaker 1: conviction that there's you're never going to completely take away
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  Speaker 1: the human element and so being able to have the
• 14:30
  Speaker 1: you know, really you know, tangible, unbiased data to understand
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  Speaker 1: when human behavior introduced risks, you know, is you know,
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  Speaker 1: something that we're always going to be able to do.
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  Speaker 1: And I think as we see more and more innovation,
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  Speaker 1: there's going to be you know, continued investment in more
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  Speaker 1: camera views you know, uh, facilities built out really with
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  Speaker 1: the focus of having technology like ours and many other
• 14:54
  Speaker 1: places in place, and that's just only going to expand
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  Speaker 1: the use cases that we can support and sort of
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  Speaker 1: the interaction between more automation and humans that really are
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  Speaker 1: going to ensure that these facilities are always operating as
• 15:04
  Speaker 1: they need to be.
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  Speaker 2: I think that's one thing that we see at Meebach,
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  Speaker 2: especially when we're looking at a lot of these new
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  Speaker 2: facility designs that we're working with companies on, is you know,
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  Speaker 2: we have to take into account that there are these
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  Speaker 2: autonomous vehicles and they are going to work one way
• 15:20
  Speaker 2: and people are going to work a different way, and
• 15:22
  Speaker 2: having those two differences in the way the work gets accomplished,
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  Speaker 2: managed efficiently within the space and without having so much
• 15:32
  Speaker 2: over I mean, there's there's going to be overlap, but
• 15:34
  Speaker 2: without having too much interference with the other because if
• 15:38
  Speaker 2: you're having to cross lines then it's not efficient. And
• 15:41
  Speaker 2: you know, the more it can work in tandem and parallel,
• 15:44
  Speaker 2: the better things flow throughout the warehouse. So I imagine
• 15:48
  Speaker 2: that that's also what you're seeing when you're looking at
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  Speaker 2: some of these you know, maybe more holistic views from
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  Speaker 2: these video feeds is how this works and maybe where
• 15:59
  Speaker 2: things need to be optimized differently in order to make
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  Speaker 2: it safer. Is that an accurate statement?
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  Speaker 1: I think that's spot on. I think just you know,
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  Speaker 1: sort of as a side note impiling onto your comment,
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  Speaker 1: I toured a terminal facility. The other data is introduced
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  Speaker 1: an immense amount of automation with massive, massive amounts of machinery,
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  Speaker 1: and frankly it's you know, it's changing their operations, but
• 16:20
  Speaker 1: it's introducing entirely new factors around safety protocols and protocols
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  Speaker 1: in general that you know, sort of an unbiased data
• 16:29
  Speaker 1: set like ours, and understanding how that automation is functioning
• 16:34
  Speaker 1: with the way things have done traditionally and the way
• 16:36
  Speaker 1: that there's always going to need to be intervention with
• 16:37
  Speaker 1: other third parties potentially come on these facilities again opens
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  Speaker 1: up sort of a really interesting area for the intersection
• 16:44
  Speaker 1: of technology and understanding, you know, what's working and where
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  Speaker 1: there areas and continued areas to continue growing.
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  Speaker 2: Yeah, especially in these brown field type facilities where they've
• 16:53
  Speaker 2: been doing something a certain way for so long now
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  Speaker 2: that the automation has come in and making that adjustment.
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  Speaker 2: It's not just adjusting to the fact that there is
• 17:03
  Speaker 2: an automation component to that facility, but also that the
• 17:07
  Speaker 2: human element has to adapt with it. To your change
• 17:10
  Speaker 2: management point, earlier that you know, there's there's a lot
• 17:13
  Speaker 2: of training and understanding and making sure that people know
• 17:18
  Speaker 2: what their role is in the facility and along with
• 17:22
  Speaker 2: all of this automation in order to remain safe and
• 17:25
  Speaker 2: to your point, make at home and uninjured at the
• 17:29
  Speaker 2: end of the day.
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  Speaker 1: Oh, absolutely so.
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  Speaker 2: With having video component and using the security systems, that
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  Speaker 2: raises a lot of questions, especially regarding privacy. It's an
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  Speaker 2: ethical issue of you know, are we invading the individual's
• 17:47
  Speaker 2: privacy with this much visualization of every detail of what
• 17:52
  Speaker 2: they're doing throughout the day. So what does vauxhel Ai
• 17:57
  Speaker 2: do to ensure employee privacy when you are doing this
• 18:01
  Speaker 2: kind of engagement where you're watching every move. Yeah, it's
• 18:05
  Speaker 2: it's not a like topic.
• 18:06
  Speaker 1: It's something we take extremely seriously and you know, again
• 18:09
  Speaker 1: sticking through our mission, it's a lot more around driving
• 18:12
  Speaker 1: safe behaviors holistically than any sort of tracking of individuals
• 18:17
  Speaker 1: or you know, data being leveraged for any sort of
• 18:19
  Speaker 1: punitive action. So, you know a few things that we do,
• 18:22
  Speaker 1: you know, across the board that are you know, absolutely
• 18:25
  Speaker 1: fundamental to our technology. We do not do any biometric tracking,
• 18:30
  Speaker 1: so it takes the individual out of it completely. Sure,
• 18:33
  Speaker 1: we're seeing an individual performed behaviors, but you're not able
• 18:36
  Speaker 1: to track that person across the facility or you know,
• 18:39
  Speaker 1: sort of any of the big brother you know, to
• 18:42
  Speaker 1: fears that might arise from having a technology around this.
• 18:44
  Speaker 1: It's behavioral based. What are we seeing that ultimately, you know,
• 18:48
  Speaker 1: done repeated over and over across different individuals and different
• 18:52
  Speaker 1: areas facility are going to are going to lead, you know,
• 18:56
  Speaker 1: to potential risk that ultimately could lead to harm. On
• 19:00
  Speaker 1: top of that, you know, we take it a step
• 19:02
  Speaker 1: further of even taking the person out of it, so
• 19:04
  Speaker 1: enabling blurring in the sense where you actually have no
• 19:07
  Speaker 1: idea what who is performing what action, rather that a
• 19:11
  Speaker 1: person performed that behavior in this area, and you know,
• 19:15
  Speaker 1: sort of across both those examples, you know, you can
• 19:18
  Speaker 1: see individual clips that we're flagging where those behaviors occur,
• 19:21
  Speaker 1: but really where our customers are effective using our information
• 19:24
  Speaker 1: is looking at the holistic data set. So how do
• 19:26
  Speaker 1: we understand observation trends over time? How do we understand
• 19:31
  Speaker 1: sort of the proximity of incidents you know, within certain
• 19:35
  Speaker 1: areas of facility and then using that data to ultimately
• 19:38
  Speaker 1: drive larger change management instead of saying, you know, we
• 19:41
  Speaker 1: need to change behavior with this one individual person at
• 19:43
  Speaker 1: this in one exact time.
• 19:45
  Speaker 2: So what upcoming features, technologies, what else is Vauxhel looking
• 19:50
  Speaker 2: to further enhance this tool in order to you know,
• 19:56
  Speaker 2: make workplaces safer? Are there any new feature in the pipeline.
• 20:01
  Speaker 1: We have some really really exciting plans future. I think first,
• 20:03
  Speaker 1: first and foremost, you know, in June we closed our
• 20:07
  Speaker 1: Series B which really gives us, you know, the capital
• 20:11
  Speaker 1: to really go and invest and expand what we're doing
• 20:14
  Speaker 1: on behalf of our customers. So I think extremely exciting
• 20:17
  Speaker 1: time from that perspective. But you know a few of
• 20:20
  Speaker 1: the things that we're focused on, first and foremost putting
• 20:23
  Speaker 1: a little bit more sort of prescriptive insights in front
• 20:26
  Speaker 1: of our customers. So we have a huge amount of
• 20:29
  Speaker 1: data that you know, is sort of flagging the certain
• 20:33
  Speaker 1: behaviors that ultimately could lead to change. How do we
• 20:36
  Speaker 1: continue to invest more and more to really decipher that
• 20:39
  Speaker 1: information and allow it to be very bite sized insights
• 20:42
  Speaker 1: that customers can use to drive those right behaviors. That's
• 20:46
  Speaker 1: something that we do with our customers today based off
• 20:48
  Speaker 1: our support model and my team really of safety professionals
• 20:52
  Speaker 1: working hand in hand with our customers to take a
• 20:54
  Speaker 1: data set and understand how we translate it to action.
• 20:57
  Speaker 1: But I think there's a massive opportunity to productize that
• 21:00
  Speaker 1: and invest in leveraging AI to really drive some more
• 21:03
  Speaker 1: of those insights to make it easier for our customers
• 21:06
  Speaker 1: to drive action on their side. On top of that,
• 21:09
  Speaker 1: you know, I think continuing to expand the use cases
• 21:12
  Speaker 1: that we support, and so you know, we're working with
• 21:15
  Speaker 1: really innovative companies today that you know, sort of see
• 21:19
  Speaker 1: the application of computer vision at a partner like Box
• 21:22
  Speaker 1: on their facilities is sort of a gateway to you know,
• 21:25
  Speaker 1: so many different use cases, whether it's around quality control,
• 21:29
  Speaker 1: you know, understanding even more risk parameters that may exist.
• 21:35
  Speaker 1: You know, so I think just working hand in hand
• 21:36
  Speaker 1: with our customers to really understand, you know, what are
• 21:40
  Speaker 1: those what are those use cases that are going to
• 21:42
  Speaker 1: drive value, whether it's you know, just a couple of
• 21:45
  Speaker 1: quick examples working underneath loads that are extended over your head,
• 21:50
  Speaker 1: or more proximity and understanding area controls outside of a facility,
• 21:56
  Speaker 1: Are there people that are interacting in a in a
• 21:59
  Speaker 1: doctor that should be there embedding analytics that allow us
• 22:03
  Speaker 1: to review this information in the form of heat maps
• 22:07
  Speaker 1: directly in the platform and access that data in real time.
• 22:09
  Speaker 1: So I think quite a different way a few ways
• 22:12
  Speaker 1: that we're thinking about sort of investment in the future
• 22:14
  Speaker 1: and extending sort of the value proposition and the level
• 22:17
  Speaker 1: of stickiness and engagement that we're able to drive with
• 22:20
  Speaker 1: our customers.
• 22:21
  Speaker 2: What kind of limitations does this technology have in assessing
• 22:26
  Speaker 2: the safety of a particular activity or a particular area,
• 22:31
  Speaker 2: Because what we're doing is you're looking, so it's visual,
• 22:35
  Speaker 2: but there's other aspects of the work in that area.
• 22:40
  Speaker 2: Perhaps the temperature that may or may not be able
• 22:44
  Speaker 2: to be recorded from that or included in that data set.
• 22:49
  Speaker 2: You know, if you're working in a warehouse and it's
• 22:51
  Speaker 2: ninety degrees that's a safety concern. That's not just a
• 22:55
  Speaker 2: environmental comfort level, it's dangerous. Or in cold chain warehouses
• 23:02
  Speaker 2: where it's in a freezing or refrigerated and using the
• 23:05
  Speaker 2: correct obviously the PPE, but the amount of time that's
• 23:09
  Speaker 2: spent there. So what are some other aspects that need
• 23:13
  Speaker 2: to be included or considered when using this tool and
• 23:17
  Speaker 2: looking at some of this information, because it's looking at
• 23:21
  Speaker 2: well looking first.
• 23:23
  Speaker 1: Just as a Have you ever been in a negative
• 23:25
  Speaker 1: forty degree freezer in a cold chain facility?
• 23:28
  Speaker 2: Yes?
• 23:28
  Speaker 1: Yes, I have actually one lesson where thick socks whenever
• 23:33
  Speaker 1: you do that, because you always get big jacket to
• 23:35
  Speaker 1: our facility like that, but they don't give you socks.
• 23:37
  Speaker 1: That's something something that I've learned, you know, on the
• 23:40
  Speaker 1: job here. But you know, back to sort of the
• 23:45
  Speaker 1: question at hand. You know, I think one of the
• 23:46
  Speaker 1: really exciting aspects of this type of technology is the
• 23:50
  Speaker 1: amount of flexibility there is. And so you know, to
• 23:52
  Speaker 1: your point, we might not be able to capture the
• 23:55
  Speaker 1: actual temperature from a camera view, but what are leading
• 23:58
  Speaker 1: indicators that might give us an indication of temperature being
• 24:02
  Speaker 1: an issue? So, you know, are are we seeing consistent
• 24:05
  Speaker 1: usage of coats within a cold coldure facility? You know,
• 24:11
  Speaker 1: in a facility that's too hot? Are we able to
• 24:14
  Speaker 1: monitor and use our visions to make sure that there's
• 24:16
  Speaker 1: water stations approkenately set up? And these are just examples
• 24:18
  Speaker 1: that I'm throwing out, But you know, I think we
• 24:21
  Speaker 1: look at a space in a very optimistic light in
• 24:23
  Speaker 1: the sense that you know, there's really interesting ways to
• 24:26
  Speaker 1: take all this live data to understand holistically, what is
• 24:30
  Speaker 1: happening in a facility, you know, and tie it back
• 24:32
  Speaker 1: to our mission at hand, which is making sure that
• 24:34
  Speaker 1: folks have the tools and the support they need to
• 24:37
  Speaker 1: be safe in their roles.
• 24:38
  Speaker 2: And it's interesting you say that because I remember when
• 24:41
  Speaker 2: when we first met and we were talking about warehouse safety.
• 24:45
  Speaker 2: It was it was one of the things I remember
• 24:47
  Speaker 2: very vividly from my uh from when I was a
• 24:50
  Speaker 2: child and my father was working in a cold storage
• 24:54
  Speaker 2: warehouse with the freezer rooms, and I remember going in
• 24:58
  Speaker 2: there occasionally with him. But one of the things he
• 25:01
  Speaker 2: did as the vice president of this facility and operationally,
• 25:06
  Speaker 2: he was the person who made sure that the refrigeration
• 25:10
  Speaker 2: kept going and whenever it was I don't know how
• 25:15
  Speaker 2: the refrigeration works, that's not my forte, but I know
• 25:19
  Speaker 2: that there was ammonia involved in the refrigeration. And when
• 25:23
  Speaker 2: there was an ammonia leak, ems would show up the
• 25:26
  Speaker 2: fire department, you know, environmental, and they would go in
• 25:29
  Speaker 2: and they're trying to find the source of the ammonia leak.
• 25:31
  Speaker 2: My dad would go in with no ppe just he'd
• 25:35
  Speaker 2: tell them he had to go in and breathe the
• 25:38
  Speaker 2: air in order to identify and to feel the cold
• 25:43
  Speaker 2: to understand where the late link leak was. So it
• 25:47
  Speaker 2: was it was incredibly unsafe. But you know that type
• 25:52
  Speaker 2: of that type of measurement of these I mean, obviously
• 25:56
  Speaker 2: that's a one off situation that's not daily erganoma and
• 26:00
  Speaker 2: daily work. But you know, making these facilities safer is
• 26:04
  Speaker 2: you know, there's there's lots of aspects to it. There's
• 26:07
  Speaker 2: there's the smell, there's the temperature, there's there's all sorts
• 26:10
  Speaker 2: of other environmental aspects. So I'm eager to see what
• 26:15
  Speaker 2: Vauxel comes up with in the future to incorporate some
• 26:18
  Speaker 2: of those other data sets to bring in and have
• 26:22
  Speaker 2: a more and more comprehensive picture. What are their plans
• 26:27
  Speaker 2: to expand your services? So right now you're only in
• 26:31
  Speaker 2: the US. Is that that correct?
• 26:33
  Speaker 1: We're actually quite global. Oh okay, we're live on four
• 26:37
  Speaker 1: different continent or deployed on four continents I think a
• 26:41
  Speaker 1: fifth very shortly. Really it's customers that are driving us there,
• 26:47
  Speaker 1: and so it hasn't been you know, sort of our
• 26:50
  Speaker 1: intention to make a big splash going international. Previously, we
• 26:55
  Speaker 1: were taking international different facilities by customers that wanted to
• 26:59
  Speaker 1: deploy our technology generally starting in the US and seeing
• 27:02
  Speaker 1: an opportunity expand it out pretty rapidly, we were able
• 27:05
  Speaker 1: to support that. But in June of this year, we
• 27:08
  Speaker 1: did announce our intention to really go international and really
• 27:13
  Speaker 1: continue to sort of invest in that segment of our
• 27:16
  Speaker 1: business as there is just a huge amount of opportunity,
• 27:19
  Speaker 1: again driven by our customers, to extend our footprint.
• 27:22
  Speaker 2: Do you find that the different safety regulations in different
• 27:27
  Speaker 2: geographies has an impact on what it is that you're
• 27:31
  Speaker 2: looking for. I mean, obviously not every geography has the
• 27:36
  Speaker 2: same safety standards or regulations, But if we're looking just
• 27:41
  Speaker 2: to make sure that everyone gets home safely, the regulation
• 27:45
  Speaker 2: really doesn't matter. I mean, it does at the end
• 27:47
  Speaker 2: of the day, and there are companies that are looking
• 27:49
  Speaker 2: to make sure that they stay within those regulations. But
• 27:53
  Speaker 2: does that factor into any of the measurement or data
• 27:58
  Speaker 2: comprehension that you're working with.
• 28:00
  Speaker 1: So I think there's there's continued opportunities and things that
• 28:03
  Speaker 1: we're doing with customers to you know, sort of make
• 28:06
  Speaker 1: the data set at their site or their their their
• 28:08
  Speaker 1: geo more relevant to metrics that matter most for them.
• 28:13
  Speaker 1: But I think you know to your question, you know,
• 28:15
  Speaker 1: I don't. We don't really too hung up on you know,
• 28:17
  Speaker 1: we're going to forecast risk based off of this regulation
• 28:20
  Speaker 1: in this country. In this country, We're going to look
• 28:23
  Speaker 1: at the behaviors that you know, we have a strong
• 28:25
  Speaker 1: conviction and working with the large amount of customers that
• 28:28
  Speaker 1: we we have in the massive data set that we
• 28:30
  Speaker 1: have to trein our models of behaviors that actually, you know,
• 28:33
  Speaker 1: put humans at risk, and so regardless of where that
• 28:35
  Speaker 1: facility is, we'll be able to provide those those insights.
• 28:39
  Speaker 2: You know.
• 28:39
  Speaker 1: Back to your original point, though, there's probably some some
• 28:41
  Speaker 1: opportunity as we you know, really work with more and
• 28:44
  Speaker 1: more customers in these areas to even fine tune the
• 28:47
  Speaker 1: type of insights that we provide a bit more. You know,
• 28:50
  Speaker 1: how does how does a company in the United States, Uh,
• 28:53
  Speaker 1: you know, sort of stay in compliance with ocean regulations
• 28:56
  Speaker 1: relative to another country. Sure, there's there's probably more to
• 28:58
  Speaker 1: do there, something exciting, But when we think about forecasting risk,
• 29:02
  Speaker 1: it's really much more around the human element versus you
• 29:06
  Speaker 1: know what what what regulations may exist in certain markets.
• 29:10
  Speaker 2: Well, and I love this, this dichotomy of using AI
• 29:15
  Speaker 2: to ensure human safety. I think that's that's a fantastic
• 29:20
  Speaker 2: use for the technology. So what do you see the
• 29:23
  Speaker 2: role of AI in the workplace safety evolving over the
• 29:27
  Speaker 2: next five ten years.
• 29:28
  Speaker 1: Yeah, I think one one side note first, and just
• 29:30
  Speaker 1: sort of that that theme of as we like to
• 29:32
  Speaker 1: call it, you know, within Vaxal AI for good, it
• 29:35
  Speaker 1: attracts you know, sort of really motivated folks. If I
• 29:38
  Speaker 1: look across some of the technical members and our team
• 29:41
  Speaker 1: that are really excited about the mission of building AI
• 29:45
  Speaker 1: for that purpose, for that intent, something that's extremely talent, tangible,
• 29:49
  Speaker 1: and you know, ultimately has those extremely positive outcomes. It's
• 29:53
  Speaker 1: not here to uh, to outsource or you know, to
• 29:57
  Speaker 1: do any of those. It's it's here to get people
• 29:58
  Speaker 1: long safe. And so that that mission is you know,
• 30:01
  Speaker 1: just as a sort of again a side note, you know,
• 30:03
  Speaker 1: really drives a lot of people to what we're building here.
• 30:08
  Speaker 1: You know, I think there's a lot of folks buy
• 30:10
  Speaker 1: better better than me to forecast what the future looks
• 30:12
  Speaker 1: in terms of in terms of AI. I think it's
• 30:14
  Speaker 1: just it's pretty incredible to see, you know, just how
• 30:17
  Speaker 1: rapidly you know, things are iterating and progressing and maturing.
• 30:23
  Speaker 1: You know, it's when I think about our business it's
• 30:25
  Speaker 1: you know, how do we you know, even more seamlessly
• 30:27
  Speaker 1: sort of deploy use cases, you know, even quicker and quicker?
• 30:32
  Speaker 1: How do we surface you know, more tangible insights from
• 30:35
  Speaker 1: ourder data sets and relay that information to customers in
• 30:38
  Speaker 1: a way that's extremely easy to digest and lead to action.
• 30:41
  Speaker 1: And so, you know, I can only can only imagine
• 30:43
  Speaker 1: what we're going to be seeing five years from now.
• 30:45
  Speaker 1: I imagine I can't even comprehend it right now, but
• 30:48
  Speaker 1: it's it's an extremely exciting time to be in this space.
• 30:51
  Speaker 2: You know what, if we had said five years ago
• 30:53
  Speaker 2: that this is where we were going to be today,
• 30:55
  Speaker 2: we wouldn't have believed it. The world is changing so
• 30:58
  Speaker 2: fast in our industry, especially now that it's front and
• 31:02
  Speaker 2: center of everyone's attention. So I'd say, you know, I
• 31:07
  Speaker 2: guess one of my last questions is what is probably
• 31:11
  Speaker 2: the best customer use case story, the best result that
• 31:15
  Speaker 2: you've been able to achieve for one of your customers
• 31:19
  Speaker 2: using this technology and helping them improve their employees safety.
• 31:23
  Speaker 2: I mean, there's got to be someone who had some
• 31:26
  Speaker 2: really big aha moments and was able to really tighten
• 31:32
  Speaker 2: up and make things better for their employees.
• 31:35
  Speaker 1: Yeah, I think I'll mention two examples, you know, one
• 31:39
  Speaker 1: very tangibly measured and extremely safety focused. You know, we
• 31:43
  Speaker 1: were working with a customer that had some pretty catastrophic injuries,
• 31:47
  Speaker 1: you know, had pretty high exposure from a claim's perspectives
• 31:51
  Speaker 1: as a result, and you know, generally speaking to this
• 31:54
  Speaker 1: was something that they had to invest in and sort
• 31:56
  Speaker 1: of through our data and you know, they had a
• 31:58
  Speaker 1: good sense this beforehand, but our data really you know,
• 32:02
  Speaker 1: drove home exactly what they need to focus on. It
• 32:04
  Speaker 1: really was around you know, sort of vehicle uh, vehicle
• 32:09
  Speaker 1: related incidents and use cases within within a warehouse environment,
• 32:13
  Speaker 1: blowing through no stops, you know, not clear drive lanes.
• 32:17
  Speaker 1: You know, the proximity monitoring was sort of was was
• 32:20
  Speaker 1: was spiking and so you know, we had a customer
• 32:23
  Speaker 1: that really over indexed and you know, sort of re
• 32:26
  Speaker 1: engineering their facility to have clear drive lanes. You know,
• 32:30
  Speaker 1: instilled a very you know focused safety program on you know,
• 32:35
  Speaker 1: training the right ways to use and even had people
• 32:38
  Speaker 1: out on the floor that were monitoring no stops you know,
• 32:40
  Speaker 1: on sort of rotating shifts. Over invested in making sure
• 32:43
  Speaker 1: that making sure that that vehicles were operating the way
• 32:47
  Speaker 1: they're supposed to. And you know, year over year they
• 32:49
  Speaker 1: were able to drive their claims data down in one
• 32:51
  Speaker 1: location alone by over two million dollars. And so you
• 32:55
  Speaker 1: know that's obviously from an ROI standpoint, you know, based
• 32:59
  Speaker 1: off of you know, them investing our technology, quite positive.
• 33:03
  Speaker 1: But more importantly, those represent you know, what would have
• 33:05
  Speaker 1: been claims, which means something had happened that wasn't supposed to.
• 33:09
  Speaker 1: So you know, that example alone, you know, was just
• 33:13
  Speaker 1: able to show sort of what is possible with the
• 33:15
  Speaker 1: right change management and focus using technology like ours. One
• 33:18
  Speaker 1: other one, I'll keep this example a little quicker, but
• 33:20
  Speaker 1: I love to focus on sort of the intersection of
• 33:22
  Speaker 1: operations and safety. We had a customer that noticed a
• 33:27
  Speaker 1: huge number of ergonomic incidents spiking about three hours into
• 33:30
  Speaker 1: a shift on two conveyor lines tied to two different doctors.
• 33:33
  Speaker 1: They're sort of looking at the data as an anomaly,
• 33:35
  Speaker 1: what's going on? Why is ergo just happening right here?
• 33:38
  Speaker 1: It took a step back and they realized, hey, we're
• 33:41
  Speaker 1: actually directing trucks with all of our heavy product skews
• 33:45
  Speaker 1: to these two doctors only, and every other doctor is
• 33:49
  Speaker 1: essentially moving pillows at the light step of a better example.
• 33:53
  Speaker 1: And so, you know, two hours in every shift, the
• 33:55
  Speaker 1: folks that were working these conveyors were just completely fatigued, strained,
• 33:58
  Speaker 1: and it was leading to a huge increase in you know,
• 34:01
  Speaker 1: improper motions that our leading indicators of risk. And so
• 34:04
  Speaker 1: they sort of took this data and they said, okay,
• 34:06
  Speaker 1: let's figure out better scheduling around our inbound full truckloads
• 34:11
  Speaker 1: and redistribute them across a few different doctors in the facility.
• 34:15
  Speaker 1: And doing so, you know, knock the ergo risks sort
• 34:18
  Speaker 1: of that we were flagging out of the picture, but
• 34:20
  Speaker 1: also increase their throughput quite a bit. You know, they
• 34:23
  Speaker 1: were a lot more efficient in terms of how they
• 34:24
  Speaker 1: were unloading product and moving product through their facility. And
• 34:27
  Speaker 1: so again it's sort of really interesting intersection of operations
• 34:31
  Speaker 1: and safety. And I'll say it again, a safe environment
• 34:34
  Speaker 1: is an efficient environment. An efficient environment is a safe environment.
• 34:37
  Speaker 1: So those type of insights are really interesting to see
• 34:39
  Speaker 1: as well.
• 34:40
  Speaker 2: I love that because that's not something that most people
• 34:43
  Speaker 2: would even think about or consider. Is you know, you're
• 34:46
  Speaker 2: receiving all day long, and you're receiving all kinds of things,
• 34:48
  Speaker 2: but what are you receiving and who is responsible for
• 34:52
  Speaker 2: receiving it and how are they able to do it
• 34:54
  Speaker 2: or are they able to continuously do it throughout the shift.
• 34:57
  Speaker 2: That's incredible insight that they may have spent years trying
• 35:01
  Speaker 2: to figure out dealing with injuries and you know, claims
• 35:06
  Speaker 2: and employees out and having to you know, higher temporary
• 35:10
  Speaker 2: staff or higher additional staff. I mean there's there's a
• 35:13
  Speaker 2: huge operational opportunity costs there that you're saving them from
• 35:18
  Speaker 2: having to spend.
• 35:19
  Speaker 1: Yeah, absolutely, absolutely, all.
• 35:22
  Speaker 2: Right, Well, thank you so much, Jack for joining us
• 35:26
  Speaker 2: today and telling us more about your company's product and
• 35:30
  Speaker 2: the safety that you're able to help companies achieve for
• 35:34
  Speaker 2: their employees. Thank you so much for joining us.
• 35:37
  Speaker 1: No, thanks for having me, Alan, It's great to be here.
• 35:39
  Speaker 2: So it's quite the step away from zero days in
• 35:42
  Speaker 2: the workplace without an injury. Stuck on a wall poster
• 35:47
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  Speaker 3: latest in supply chain information. Thanks for listening. Until next time.