Powering the Future of Shift Work with AWS and HyperTrack

In this Shift Work Summit session Manish Govil, Industry Growth Manager at AWS discussed how AWS enables companies to streamline operations and enhance worker productivity. AWS’s powerful cloud infrastructure serves as the foundation for teams building solutions for on-demand and flexible workforce models. Ram Kakkad, VP of Product at HyperTrack discussed how HyperTrack supports each stage of the shift work lifecycle, providing operations and management teams the data they need to validate work completed and make decisions. The demo of HyperTrack’s operations views, led by Aashish Subramanian, Director of Engineering at HyperTrack, highlighted how AWS infrastructure is the backbone of HyperTrack’s platform of APIs and SDKs that provide logistics intelligence for workforce solutions across various industries, from healthcare and retail to light industrial and oil & gas sectors.

Watch the following highlights and view the full video and transcript below.

Flexwork is on the rise (2:19)

How HyperTrack leverages AWS (4:56)

How HyperTrack location intelligence supports shift work (7:26)

The three stages of the shift work lifecycle (11:26)

Demo: A Day in the life - The HyperTrack operations view (14:58)


Gaurav Deshpande: Welcome to the last session of the Shift Work Summit. As promised, I've saved the best and biggest session for last. I'm your host, Gaurav Deshpande. It's my delight to welcome HyperTrack's biggest partner Amazon here. Since inception, HyperTrack has built its cloud infrastructure on AWS rails. Over 80% of our more than 350 customers now are on AWS as their cloud. Many of the shift work marketplaces in the audience today are running on AWS as well.

It's my pleasure to welcome my friend Dr. Manish Govil, Industry Growth Manager at AWS, along with our very own Ram Kakkad, HyperTrack's VP of Product. Manish and Ram will share how HyperTrack and AWS are building the future of shift work together. We also have a wonderful demonstration of HyperTrack's location intelligence technology from Aashish from our engineering team.

Manish Govil: Thank you, Gaurav. It's wonderful to be here with you at the Shift Work Summit. As we've heard from all the speakers today, flexwork is growing at a rapid pace. Ram, Aashish, and I are thrilled to share how AWS and HyperTrack are powering this movement.

So what is all this excitement about flex work? Well, the nature of work itself is changing. Technology has revolutionized how we work and where we work from, and people are redefining how work gets integrated into their lives. If you look at the report from staffing industry analysts, the size of the flex work industry is approximated to be about 3.8 trillion dollars. Wow! That's a big number, and there's a good reason for it.

Flexwork is on the rise

"So it's no surprise, then, that this flex work economy is 3.8 trillion dollars worldwide and growing rapidly."


We need flex workers every day in our lives. The Uber driver that drove you to the airport is a flex worker. The Doordash driver who brought your delivery is a flex worker. Companies like Amazon hire thousands of flex workers every year to meet fluctuating needs. Well, walk into any conference venue, stadium, or hotel, and over 50% of those employees are workers hired for specific shifts.

So it's no surprise, then, that this flex work economy is 3.8 trillion dollars worldwide and growing rapidly. What has made flexwork appealing to workers is the technology that has simplified how they engage in it. And that is why over 17 billion dollars of investment has gone into talent platforms, technologies like the shift work marketplaces which make it possible.

This is leading to an Uber-like effect in many industries, from retail hospitality, industrial and healthcare. You had speakers from many of these industries today as part of the summit. The workforce for flex work is growing twice as fast as that for regular work, and this is the reason workers prefer flex work. That reason is the choice and control flexwork offers workers over their lives. They can work from where they want, when they want, pick which work they want based on what they're going to get paid for it.

How HyperTrack leverages AWS

"We provide scalable, reliable and cost-effective cloud technologies to power flexwork. Location intelligence tools like HyperTrack run on AWS cloud, tapping into location data and analyzing it for actionable events such as a no-show of a shift worker or early departure from a shift. Location intelligence can help improve business outcomes, to reduce no-shows, backfill missing workers and provide shift verification so the workers can be paid faster."

With this in context, it's no surprise that work is exploding in the flexwork area. Let's look at how AWS and HyperTrack are powering the backbone of this flex work economy, which is the shift work marketplaces.

A two-sided marketplace, like Workwhile or Nursa, connects employees, whether it's warehouse workers in case of Workwhile, or nurses in case of Nursa with employers on the other side, at warehouses, in the hospitals. This offers workers the flexibility they want, and allows employers to fill shifts with verified workers with a click of a button.

Underlying all of this is the technology that holds the data and the applications connecting the employees with employers work it by these marketplaces. This is where AWS comes in. We provide scalable, reliable and cost-effective cloud technologies to power flexwork. Location intelligence tools like HyperTrack run on AWS cloud, tapping into location data and analyzing it for actionable events such as a no-show of a shift worker or early departure from a shift. Location intelligence can help improve business outcomes, to reduce no-shows, backfill missing workers and provide shift verification so the workers can be paid faster.

Let me now hand it over to Ram Kakkad, HyperTrack's Vice President of Product to share how HyperTrack adds location intelligence to your platform. Ram, over to you.

Ram Kakkad: Thank you so much, Manish. It's great to be here, and it was super inspiring to hear all the speakers ahead of me. I'm lucky to be in this session and stand on the shoulders of the giants before me who set a super context for me to speak about what HyperTrack does, and how we partner with AWS! And of course, after me, I'll be introducing Aashish, who's our director of engineering to walk through a demo to see how this all comes together.

So just to recap the day a little bit before I get in, we've all heard about how it's really critical for any shift work marketplace or flexwork business to be able to track their worker pre-shift, on-shift and post-shift, and some of the things that come up to mind in the pre-shift space. Yeah. So there are different questions that customers need to answer at every stage, and we'll walk through a little bit of that as we go in terms of how HyperTrack can help you answer some of the key questions.

Before I get there, one of the things I want to call out is that everybody here who's part of this conference or interested in this space is a technology builder for the market that we're in, which basically means that you have way better knowledge about how your customers need to interact with technology and what role and where location should actually get into that experience.

How HyperTrack location intelligence supports shift work

"HyperTrack provides you embeddable views which you can simply add in a low code way to your view, so simply create like a shift replay, if you will. Right there, or you could use our web hooks to add very critical signals, like is the worker at risk of a no-call, no-show, or did the worker leave early, or, if the work actually happened as expected. "

And so what HyperTrack does for you is it lets you add location intelligence to your experience as you've envisioned it. We do not force you to have our experience. It is your control. It is your opinion for your customer, and we expect that we'll be able to add into it within your native experiences as defined.

And all that comes together really through four components that we envision, we visualize. One is on your side, you have a shift management system that basically tracks what shifts you have and which workers are going to do them. That interacts with the HyperTrack cloud and the HyperTrack cloud orchestrates movement of location data across 3 primary experiences, which is the Ops experience, the worker experience and the customer experience which is optional in some cases. And let me walk through how we do some of this in our product.

So on the shift management side, you'll basically interact with HyperTrack's APIs, and we really have 3 main APIs that would be of major interest. There's the Orders API, which lets you tell us what a shift shape and destination are. So for example, if you have a worker who wants to go for a 9 to 5 shift to a particular destination, you'd basically just need to tell that to us in the Orders API call for us to track it.

Before you can even track a shift, though, you do have to set up your workers and your places, and so HyperTrack provides you APIs exactly for that. You have the Places API, which lets you define your customer destinations. And over time HyperTrack will start inferring intelligence about these places. So you know what their actual shape on the ground is, and that can help you automate signals about when the worker's arriving, clocking in or leaving and clocking out more accurately.

And finally, you also have the Worker API, which, as the name suggests is the API that you'll be able to use to manage your workers' lifecycle, mapping them to a device that they're using, which has your worker app in it which has the HyperTrack SDK embedded in it. All of that can be done through the Worker API.

Now the Ops experience is where the magic kind of comes together. You have your own control tower where all your shifts are being monitored. And you have multiple ways in which you can interface with HyperTrack to enrich that with location intelligence. HyperTrack provides you embeddable views which you can simply add in a low code way to your view, so simply create like a shift replay, if you will. Right there, or you could use our web hooks to add very critical signals, like is the worker at risk of a no-call, no-show, or did the worker leave early, or, if you know, the work actually happened as expected. And now this is good to pay automatically.

So all of that can be built in or embedded as you need depending. And you know, for a company that's starting out or may not know exactly how this all comes together, you could initially start just by using the HyperTrack dashboards, which is a zero-code way, essentially for you to get started with location intelligence.

Now, the worker experience is where this becomes very interesting, because again, you don't need to have the HyperTrack app as part of your experience. You can simply embed our SDK, we support multiple platforms, native Android, iOS, Flutter, React, and all the popular ones. We also have our out-of-the-box apps in case you just want to get started without integrating the technology. So all of these are ways in which you can get to market fast and see how location intelligence can impact your business. And we love working with builders who have a strong opinion on how the experience should be. But we give you very easy on-ramp to piecemeal figure out which experiences you want to actually build together.

And finally, in some cases you might have an end customer experience as well. So in cases where there are shifts that are end-consumer-related. For example, we work with home repair companies that have workers going to the home to repair, repair crawl space and things like that. And for that you need to provide end consumer tracking links, for when the worker is gonna arrive and things like that, those can also be done in the B2B space that's less relevant. But it is an option that you do have.

So going forward. Now, when it comes to actually managing the lifecycle of the shift that multiple speakers before me have already alluded to. There's really three parts of the lifecycle that we need to get together, which is the pre-shift experience, the on-shift experience and the post-shift experience, and the questions that a business owner such as yourself would need to answer at these stages are very, very different.

The three stages of the shift work lifecycle

So pre-shift is on the day of the shift. Is the worker gonna reach on time? Is there a no-call, no-show risk? And how can you find a replacement if you do? You know the eventual situation does occur where the worker has finally canceled and HyperTrack provides you multiple solutions in this space. So obviously live location is one of the most critical signals for you to be able to detect a no-show, no-call, no-show risk.

We use location intelligence and live location to know if the worker is obviously reaching the destination on time, or we also track risks like the worker moving in the wrong direction, indicating that they're not intending to move towards the desired location, which can then trigger workflows on your side to reach out to the worker via own means to understand if the situation has changed, or if they cannot make it, some last minute emergency has come up, and they've not been able to inform you.

And this lets you then kick off workflows to find a replacement where HyperTrack has an API for you to find nearby workers who might be available. And we can return to you a list of workers who are closest and who can get there in quick time, and you can, of course, then choose which of the close by workers you'd like to give the work to depending on skill set ratings, and whatever other business logic that you have.

And of course, if the worker is not going to reach on time, then you can have multiple types of interventions there. You can inform the shift manager that you know a certain worker from the fleet might be reaching a certain amount late prevents them having to reach out to you to ask if the worker is going to come. I used to work at Amazon, and one of the kinds of things there was the best customer contact is no contact at all. And so the more you can automate and preemptively tell customers that something's gonna change from what they expected, the less they'll have to reach out to you, and they can plan for it.

On-shift tracking is another interesting case, because if it's a 9 to 5 shift, and you're going to pay out expecting the worker was there for the whole time. You need to make sure that the worker was actually there the whole time, because ultimately that's what you're paying for and on-shift lets you track automatically if the worker was on-site through the duration of the shift. We track entries and exits to the destination in real-time and web hook them back to you. We aggregate the time the worker actually spent on-site during the shift tracking. And that lets you kind of guess automatically that the worker has actually done the site, done the work as expected. And you finally also track, you know, when did the worker finally leave? Because sometimes they may have even extended their stay, and they might be needing to claim overtime. And so you know, knowing when the worker finally left, and all of this is controlled again via granular API calls which let you control when the shift is expected to start and expected to end and everything can be controlled relative to that plan.

And post-shift, I think we've heard a lot about validation of jobs and automatic payment pretty much within seconds of the shift, or even sooner. We're constantly improving that you'll pretty much know if the work actually happened as per plan? Did the worker arrive on time? Did he spend as much? He or she spend as much time as expected on site? Were they visible throughout in terms of location? Availability? How much mileage did they actually run? We heard a lot about sales tracking and mileage in one of the previous sessions from
Sunderstorm. So again, that's just given back to you within an instant of the shift actually ending.

So to show you this I prefer to show and not tell. But now that I've told you what you're likely to see, I'd like to invite Aashish, who's our director of engineering. He actually had the chance to record his demo, which I will play shortly for you, but he is available on the call to address questions. And so I will start playing that video right now.

A Day in the Life - The HyperTrack Ops View


Watch the demo of the operations view of two of the most common time and attendance scenarios - worker left early and no-shows. Aashish Subramanian, Director of Engineering at HyperTrack will show examples of what operations teams see when identifying a worker who left a worksite earlier than the scheduled end time of a shift and the situation when a worker does not arrive to the work site at the scheduled time.

Ram Kakkad: Thanks so much Aashish. I think that clarifies a lot about how the sausage is made, and how it looks. Would love to open the floor for questions and hand it over back to you, Gaurav.

Gaurav Deshpande: Yes, thank you, Aashish, for the hard work that went into recording the video. I know building the product is a breeze for you. So I'm not gonna say that's a hard one. That's a labor of love. But building videos is not your day job. But you did a wonderful job. So thank you for capturing how HyperTrack location intelligence allows you to flag a no-show where the worker doesn't show up for a shift, how you can flag the tricky situation of worker left early where the worker leaves early and still wants to get paid for the entire shift.

The whole objective there was to provide indisputable location intelligence data that can help you pay appropriately, pay fairly based on what the worker has done, and the same thing from the worker's part if they forgot to clock in. But HyperTrack has still clocked in their location, then they can get paid despite the onsite system saying something different.

So this is wonderful. There are a few questions to walk through from the chat. The first question, for you, Ram, and then there's a question for Manish. A question for you, Ram: What is the typical process of integrating the HyperTrack location intelligence into a shift work marketplace?

Ram Kakkad: Yeah. So we like to keep it fairly simple. We need to understand the business value that the customer is looking for, and then do a quick solutioning exercise to figure out which, like I mentioned, HyperTrack provides different ways for you to get started really fast depending on which parts of the experience you want to control. So I think, doing a quick solutioning exercise to see which SDK or mobile experience you should power with which operational experience you should power and which API you should use typically takes about a day or two with some back and forth, you know, depending on how defined the scenarios are.

And then, yeah, we basically get into a working, a partnership mode where it takes, you know, getting a hello world done usually takes like a day or two, and of course there are many more things to be taken care of when you're moving to production, and that can take a couple of weeks. So yeah, it's fairly simple. We've generally had great feedback from customers who integrated with us and been able to go to market really fast.

I think the fastest I've seen something go to production is from idea to production and revenue, which is a new product launch, was 6 weeks.

Gaurav Deshpande: Wow, okay. Zero to full launch product launch with the revenue in 6 weeks. That's incredible. I take it that's probably Pagarbook Geo that spoke in the morning, the first session of the day. It's wonderful to see that kind of velocity. The next question is for you Manish. Over on the AWS side as you look at this, you see the expansion in flex work. And as you work with partners like HyperTrack, what are some of the things that you are seeing from your perspective? Because you have a much broader perspective of industries across multiple industries and across multiple geographies. How do you see flex work evolving over the next decade?

Manish Govil: So I think it's a natural evolution that we have seen over time, right?

So when you think about it, what makes things attractive in one sense are some time of concern as well. Right? So people want to be identified right? Hey? I'm here. They should know I'm here. So that's the ease and experience part. But then you also talking about the privacy and security right? And and sometimes you can have a false sort of a competition between the two. But it doesn't have to be. Because I think with the the digital technologies that we have like, for example, location, it can be a dispassionate and data driven and secure transaction where you can achieve both of these things. Right? So I think, as technology evolves, the experience is continue to go to evolve the speed at which these things happen continues to evolve, and and an AI plays a a good part. I think John touched upon a little bit that we. We are now manually defining what location is. As we learn more, some of it can be automated.

And other things can be automated right? We talked about paying fast, finding workers who are close by. I think those are the type of things that can keep evolving, that you can come up with suggestions, saying, hey, here are things right now.” We have a a certain fidelity that we can provide with as we grow those things can become, much more meaningful from both a suggestion, perspective, and as well as in terms of how you contact each one of those sites. How do you issue those alerts? How do you contact people? You have AI-based Chatbots that are basically evolving. There's a lot of things that can actually come and wrap around the Location Intelligence service that we talked about today.

Gaurav Deshpande: That's wonderful. And on that note I'm gonna close out the Shift Work Summit, just to remind everybody: If you want to add location, intelligence to your shift work marketplace, please go to hypertrack.com, click on request a demo where you can see a custom demo of our products. Schedule that meeting or sign up for free, where we have a free trial, where you can integrate HyperTrack’s,location intelligence API  into your shift work marketplace and test it out quickly. Integration is very quick, and we would love for you to test it out along with 350 other customers who are using it around the world.

Thanks a lot. Have a wonderful rest of the day. Thank you for joining me, and we will see you back next year for the Shift Work Summit 2025. Thank you.

For more sessions on the technology shaping shift work, please visit the Shift Work Summit session replay page.