How SharkNinja Builds Agents that Work with Real-World Data

Let's welcome Carolyn Derkopp, Technology Transformation Partner at SharkNinja. We're so excited that you can join us. Welcome.

Thank you so much for having me. It was so inspiring to hear Oliver and Imran's story, and I'm really excited to share what we've achieved at SharkNinja.

I'd love to hear what you're doing at SharkNinja with AsiaForce.

Great. So at SharkNinja, we create innovative home appliances from Shark vacuums to Ninja air fryers. We've actually got 39 product categories.

Wow.

And we've now also got a number of different Agentforce agents. These range from services to shopper to unboxing use cases. And actually, when we were looking at building our first agent, we were facing a pretty real challenge. At SharkNinja, we're launching about 25 new products every single year, which is obviously a hugely exciting pace of innovation, but it's also going to come with a huge demand in customer experience, so Whenever we launch a new product, there'll be new pre-purchase questions, new setup journeys, new troubleshooting flows. And what we found is that our customers experience all of those moments in a unified way. So we also wanted a unified platform to address all of those use cases, and that's where Agentforce came in. So we started with a couple of high-volume use cases at the start, like Wismo. All right. Where's my order?

Where's my order? I was gonna say Wismo.

Yeah. Then we moved into shopper pre-purchase searches, journeys, and more recently into unboxing, a more proactive use case. And actually, we brought a gift for you today.

A gift for me?

Yeah, this is the Cafe Luxe. What?

Who told you that coffee is my love language? Thank you.

We really just wanted you to be able to experience our unboxing agent just like a real customer. This is amazing.

Okay, so we're going to actually go through the— see it live.

Yeah, I'll show you exactly what it looks like.

Oh, I'm so excited.

Our products come with something like an instruction booklet which has a QR code. This is a QR code-led experience.

I love that. I love the espresso martini on the front there.

Yes. Yeah. He makes a wonderful one. So if I go ahead and scan this QR code, this is going to kickstart the unboxing agent. Right. Then as you can see, It's not a generic welcome at all. The agent already knows exactly the product that we're unboxing. The model number was passed through. And actually, this machine is a really great example of why an unboxing agent is so powerful. It's going to get you a great coffee, but there's a few very important steps that you need to do before that. Ah, okay. You've got to flush the machine. You've got to do a couple of calibration runs. You've got to find the right grind setting for your beans.

There's only one setting that counts. Strong. Yes, exactly.

And this is where guided setup comes in. So you click through all of these steps and it's going to tell you exactly what to do. And what's great is if you're ever stuck, you can also click to get more help. And on top of that, if you have any other questions about the product, you can just go ahead and type it in. So a lot of our customers might ask, what's the difference between the espresso strength options?

But you type it in and it doesn't take you out of the process of the agents bringing you through?

No, not at all. The context is going to persist. It's going to give you the question, but actually you can scroll back up and go back into your guided setup journey.

I love that.

So it was a really simple idea. We want to meet the customer in those first moments. So it's not just setup, answering questions. It's also going to give you the best recipes for an espresso macchiato. It's going to connect you to our social media. Or help you register your product.

Oh, registering is so important because I always forget. So that it's part of the process. That's great. Great reminder. I'd love to see, how did you build that agent and that whole experience?

Let me take you a little bit behind the scenes. So this is our agent. We've built this using AgentScript. It was really new territory for us. You can see here on the left are our different subagents. This one is product greeting. You saw that in action just now. It's that personalized greeting. So the QR code actually passes the model number to the agent and it's going to set the tone. A different product with a different model number will again send the right product to the agent. So it's the same agent, but a different experience. It's going to be scalable. Another sub-agent I wanted to show you is Product Assistant.

Okay.

You just saw that in action as well. This is what powers the guided setup and also those contextual questions. What's really great is that this is all powered by pre-structured data in Data 360. And also really great is that level of determinism that we have here. Really important for those guided setup steps. They have to happen in a very specific sequence, but also the flexibility to ask natural questions for the LLM to kick in. That flexibility is super important to us. Another thing I wanted to show you, flexibility of how we work in this agent has been really amazing. Right now you can see we're in Canvas view. This is the low-code visual way of building, but we also have the option to toggle to script. This is really good for our developers that want more programmatic and precise way of coding. It's the exact same agent, it's just a different view. When I first saw this, I was a little bit worried. All of our developers are trained in a different way, but actually there's so much training available, lots of powerful AI tools to help you not only transfer your existing agents but also build from scratch and troubleshoot. So something that we use is the inbuilt AI assistant. So it's really useful, for example, when we have an issue like the action isn't triggering or a variable is coming through wrong. We can ask the agent here and it's going to give you a really intelligent response and some tips on how to fix it. So that's been super valuable for our team.

That's amazing. So you guys have gone through the whole evolution of moving into the agent script and then working in a new way.

Yeah.

One of the key things to the agents performing, and I like to think of it as like a key thing to a good cup of coffee is the bean. The main ingredient for a good performing agent is data. Grounded in good data, but at the same time, too much data can be overwhelming. And so I see your amazing PDFs like that, which my husband would love because he'd read from top to front. How do you handle unstructured data with your agents without overwhelming it?

So this is actually where we use something called Intelligent Context. Here we ingest all of our product information, FAQs, instruction booklets, manuals. We do have a lot of product data still living in PDFs. Our CX partners are in the process of digitizing that. Obviously, PDF's great in print, but they're in the process of making it great for AI consumption and also digital human consumption.

Right.

And you can see why. This is an example of one of our PDFs. There's so many images, diagrams, lots of information here. And historically, this would have been super hard for an AI to understand. If you imagine you just scrape the raw text from here. Right.

Without the pictures.

Yeah. It's going to lose all that context, the diagrams, the sequencing, the images. What Intelligent Context actually does, it has an LLM run on the PDF and understand the PDF. Then it chunks the understanding and the context rather than chunking the raw text. Let me show you how that works.

I'd love to see that.

So if you remember, we asked the agent, what's the difference between espresso strength?

And we all agree that the only strength that matters is strong.

Exactly. So you can see here, this is the answer we got before in the agent as well. But I can click into the chunks that created this answer. And then I can also see the passages of where in the PDF this came from. If I open this up, It's not verbatim copy paste of the PDF, it's that understanding. And that's—

So it's the agent's understanding of bringing in that data.

Exactly. And all of the context remains here. So it's like a really verified knowledge base of this PDF.

And if you saw something there, if you were reviewing it, maybe in your processes where you have a human in a loop is that they review these chunks. If they see something that has been interpreted a little off, they can tweak it.

Exactly. And that transparency is so important. Important for a brand like Shark Ninja. So it's been super valuable.

This is amazing. I mean, just the whole process, and I love the unboxing agent. I can't wait to get home and actually use it, and I'll let you know how it goes.

Absolutely.

Thank you so much for sharing your experience with all of us here, and I'm sure many are gonna learn from it.