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This episode of The Edge of Show dives deep into how FuelIX is revolutionizing enterprise productivity with its innovative generative AI platform. Host Josh Kriger connects with Mark Denninson, Product Manager at FuelIX, to explore how their AI copilots are transforming operations across global enterprises. Live from Arlington, Virginia at the Generate event, this conversation unpacks how FuelIX—born out of TELUS Digital and WillowTree—brings together over 30 AI models like Claude, Gemini, and OpenAI under one agile toolset.

From enabling smarter documentation and bug tracking to powering IT and HR copilots, FuelIX offers tools that are not only secure but scalable for massive enterprises. Mark breaks down how AI copilots prompt the prompter, ensuring employees get answers that are actionable, role-specific, and privacy-compliant. Whether it's boosting creativity or simplifying internal systems, this is a must-listen for anyone interested in how FuelIX AI is reshaping the enterprise landscape with generative AI.

Host: Josh Kriger
Guest: Mark Denninson, Product Manager at FuelIX

Key Topics Covered:

• FuelIX AI Platform Origin Story: Learn how TELUS Digital, WillowTree, and TELUS birthed the innovation hub FuelIX to unify generative AI across enterprise operations.
• Enterprise Productivity with AI Copilots: Discover how FuelIX copilots assist in documentation, bug tracking, IT helpdesks, and HR policy lookup, saving hours of work.
• AI Model Diversity in FuelIX: FuelIX integrates over 30 LLMs including Claude, OpenAI, Gemini, and Meta, allowing users to switch seamlessly depending on the use case.
• AI Prompt Reasoning and Planning Engine: FuelIX copilots reason through vague or incomplete prompts to build actionable plans for execution—tailored to each enterprise’s workflow.
• Data Security and Guardrails: Learn how FuelIX ensures secure AI interactions through redaction, prompt-level privacy filters, and model-agnostic integrations.

Episode Highlights:

"We're bringing the best of AI into one pane of glass to make tools robust and safe for enterprises." – Mark Denninson

"It’s not just prompt in, response out. Our copilots reason through what you actually need." – Mark Denninson

"I have a story writer that knows the formatting I prefer, even placeholder text in two languages." – Mark Denninson

"FuelIX prevents data like Social Security numbers from ever reaching the model." – Mark Denninson

"The value I bring isn't just documenting features—it's imagining what's next. Copilots help me get there." – Mark Denninson

People and Resources Mentioned:

• Mark Denninson
• Josh Kriger
• FuelIX
• TELUS Digital
• WillowTree
• Claude AI (Anthropic)
• OpenAI
• Google Gemini
• Meta AI
• ZuberLawler
• Generate Conference
• Unstoppable Domains

About Our Guest:

Mark Denninson is the Product Manager for FuelIX, a division of TELUS Digital. With a background in building digital solutions at WillowTree, Mark now leads the development of enterprise AI copilots under the FuelIX platform. His focus is on helping large organizations democratize AI usage internally by integrating multiple LLMs, enhancing internal productivity, and ensuring data security. Mark is passionate about agile innovation and using generative AI to reduce friction in enterprise workflows.

LinkedIn: Mark Denninson
Website: FuelIX.ai
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Transcript:
Mark Denninson : Hi, this is Mark Denison, Project Manager at FuelIX, helping global enterprises maximize productivity using the latest in generative AI. And you're watching the Edge of Show, where you can learn how to be more productive using the latest emerging technology. Stay tuned.

Josh Kriger: Cool. All right, I'm going to try one or two things, see if I can get this right. Hi everyone, you're watching the Edge Of show. Tune in today to learn how a product manager at an enterprise AI tool is maximizing the productivity of enterprises globally with the best products and services and prompt management for enterprises. You'll also learn some of his favorite tips and tricks and where he got his passion for AI. You won't want to miss this episode. Stay tuned.

Intro/Outro: Welcome to The Edge of Show, your gateway to the Web3 revolution. We explore the cutting edge of blockchain, cryptocurrency, NFTs, ordinals, DeFi, gaming and entertainment, plus how AI is reshaping our digital future. Join us as we bring you visionaries and disruptors pushing boundaries in this digital renaissance. This show is for the dreamers, disruptors, and doers that are pumped about where innovation meets culture. This is where the future begins.

Josh Kriger: Let's take a pause to shout out one of our favorite partners. For tech innovators facing legal challenges, Zublaudler is your go-to law firm. They focus on understanding your technology and business model before addressing legal requirements. Specializing in blockchain, AI, VR, AR, quantum computing, and more, ZuberLawler offers expert guidance in capital raising, IP transactions, M&A, litigation, and compliance. Visit ZuberLawler.com, that's Z-U-B-E-R-L-A-W-L-E-R.com for cutting edge legal solutions. Hi everyone, Josh Krueger here, co-host of the Edge of show live in Arlington, Virginia today at the Generate event. It's a interactive workshop educational conference where leaders across industries are learning about how to apply AI to their companies, to their government organizations, to their lives. And we're here with one of the partners for that event, Mark Denison, who's the product manager at FuelIX, a division of Telus Digital. It's great to have you on the show. Yeah, thanks for having me. So we'll dive into what you're up to. But first, maybe just give us a little bit background on your organization and what brings you to this particular event.

Mark Denninson : Sure, so like you said, I'm the product manager for Fuel IX, specifically CoPilots, our product CoPilots that is about bringing AI, democratizing AI across organizations. So bringing CoPilot tools to life within the entire employee base of an organization. So, you know,

Josh Kriger: I am based in Charlottesville, Virginia, out of a company called... I went to William & Mary, so it's not too far away. It was a little bit of a rivalry there, for those that don't know, UVA.

Mark Denninson : Indeed. So, you know, I started working at a company called WillowTree, which is a division of TELUS Digital, and since then have sort of shifted over to this Fuel iX innovation lab that is specifically around bringing these AI tools to life. You know, I think where it came from in terms of the history of FuelIX is WillowTree, Telus Digital, and Telus all sort of were creating, starting to create their own AI solutions, each for themselves, each doing a little bit of what each other were doing, but also kind of different things here or there. And this is fuel was sort of born out of that, of kind of how do we do this in a more agile, you know, in a more agile way for us. And how do we then bring it to other people? Because we were sort of on the, on the forefront there. And so if we need it, other organizations like this are going to need it. If we can do this for TELUS, an international, global telco company in a highly regulated industry and stuff. If we can do it for them, we could do it for

Josh Kriger: No, that's great. I mean, we've definitely had more and more interactions with telecom companies across the globe at different events, you know, who have this unique sort of opportunity with the scale of their customers and their networks to innovate and to go into new product lanes. You know, for example, STC in Saudi Arabia does all sorts of fun stuff in robotics and AI and whatnot outside of just pure telecom. So that's great that you guys are pushing the boundaries there. What personally got you excited about AI? When did your AI journey personally began where you're just like, oh, man, this is amazing stuff. I want to spend all my time focused on it.

Mark Denninson : I gotta tell you, I don't know that I had an instance like that. I was working on many different programs while at Willowtree as part of many different kind of Telus-related programs and got pulled into Fuel knowing almost nothing about generative AI, certainly never having worked in it directly. I had been paying attention to you know, the release of Challenge UPT and all that kind of stuff. But never, it wasn't my, you know, it wasn't something that I went out and necessarily sought. I sought working with some of the folks that happen to be on this program. But once I got into it, I mean, I am full convert at this point. I use our tool every day. I use our similar tools around the web every day as we come up with these kinds of solutions.

Josh Kriger: Well, it's very cool. So we'll go into your solution, but I consider myself a heavy prompter at this point. I do use Perplex AI a lot. You mentioned to me before we started that you guys work with over 30 different AI LLMs. That's right. you know, can you educate our audience on maybe some of those LLMs out there that you think are pretty novel and maybe not the ones that people hear about every day in the news that even integrate into your solution that people should take a peek at?

Mark Denninson : Yeah, I will say across all of Fuel, but especially, it's especially relevant to the co-pilot product. We are bringing, like you said, the sort of the best of AI into one, one paint of glass, so that we are able to deliver those, you know, make those tools robust, make those tools safe for enterprises to roll out to all their customers or all their employees, I guess.

Josh Kriger: I assume some of these tools are harder to access and also if you're going to use all these tools it gets expensive and complicated.

Mark Denninson : That's right. I mean you could go out and pay for a license for each one of these. Adds up. um uh and that will add up or you could be part of fuel and you could get access to all those so you know what are most examples of some of the like precise tools that are in your toolkit sure so we have different models so you could build a co-pilot that is pointed at one of, largely we limit specific copilots to four models. Meta, OpenAI, Gemini, and Clawed. So Clawed is the one that we generally use. It's our sort of all-purpose model under the hood. It's the one that if people don't know where to start, we say just leave it at Claude and let it take care of it. If there's no reason you need to go use an OpenAI model for something specific, don't worry about it. Just use this. Don't even think about the model underneath. We also, you know, bring our own tools that we've curated as well. So we've created a planner executor on top of those models. So no matter which model you choose, Fuelix is going to take your prompt, it's going to do some reasoning to figure out what it is that you actually want. What are you trying to get out of this interaction?

Josh Kriger: Yeah, because sometimes we, I don't know, we prompt without knowing what we're really looking for. So it's kind of like you're prompting the prompter.

Mark Denninson : That's exactly right. So it's taking that initial prompt that you've put in, maybe it has spelling errors, maybe it's half of a thought, or maybe it's lacking some other sort of related content that you might not have actually thought to give, thought to put into that prompt. And so it will do some reasoning around that, then it'll plan, it'll make a call to the API to make a plan for how to respond. And that plan might be to choose to do some other tool calling, go out and search the internet or create an image or build a UI just straight from the prompt itself. And then it will actually complete or execute that plan.

Josh Kriger: So I'm curious, like, you know, with enterprise customers, they're always thinking about security. They're thinking about the quality of data. So we're also thinking about sort of IT protection, right? So how do you balance these concerns while delivering the most robust product possible?

Mark Denninson : Yeah. So we, um, you know, that is, that is the core mission of all the fuel of all of the products that are, that are out there is that we, we know those concerns that, that our clients have. We know that security is a, is a big concern. One of the, one of the benefits not only to the the user is going to benefit from having access to all these models without having to pay for a license here or there but the org the enterprise benefits from not being locked into a specific provider so you know if there's a data breach or if there's a great new feature that cloud comes out with that isn't available in open AI yet or whatever, you don't have to rewrite all of your use cases, all of your bots that you've already put out there. You can use that just, you know, if you build that on top of something like fuel, you could swap out all those underlying pieces. We don't, We don't, frankly, we can guide you on which models you might want to use for each, any given use case, but we don't ultimately have, you know, a preference. We want you to be able to get the best out of, out of them.

Josh Kriger: And say there's a comment, like, look, I want to give this capability to every one of my employees, but I'm really concerned about, um, IP leaking into these models. and I'm concerned about my employees taking these ideas and running with it and not benefiting the organization. So how do you respond to those two concerns?

Mark Denninson : I would say the best way to think about that is when it comes to guardrails. So we can build in guardrails into into our platform, which basically gives the tools to the enterprise leaders to say, hey, we don't want our users talking about this particular topic, or we don't want our users uploading all of our customer data and sending that off to the LLMs. By default, I mean, just generally, nothing that happens on our platform goes to the models for training or learning or anything.

Josh Kriger: So we're not- I think that's a really important thing that people don't understand is a lot of these models don't actually take your data and go with it. They have a separate sort of data ingestion process that happens independently.

Mark Denninson : I would say, yes, that is true. Although, if you're using some of these models more directly, there is no guarantee that what you're uploading there or what you're talking to them about is going to be, is not going to be used.

Josh Kriger: Providing a bonfire, essentially.

Mark Denninson : Yeah. So we make sure, you know, there is not something that's going to be trained on the data you put in. We also prevent certain types of data from even going off to the model, not because of training, but more because of data breach kind of stuff. So, you know, we have a guardrail that you could prevent anything that looks like a social security number and just redact that out. We don't even show that to the model. It's not going to be relevant in the model's plan or response to know any particular social security number in the first place. So we just say, don't use it. Respond to the users, what the user needs, but don't use this piece of data in there.

Josh Kriger: Right on. Let's jump into some of the specific use cases. You know, there's obvious ones that people are always sort of using these models for in terms of project management or reviewing contracts or documents that can be quite tactical, right? What are some of the more interesting and novel use cases for your product that you've seen you personally use it for or that other people are using it for that maybe would sort of enlighten our audience in terms of like possibilities for AI that they might not already be thinking about?

Mark Denninson : Yeah, well, like I said about the the sort of orientation we have towards the enterprise. So we do want to make these these these tools usable and valuable to all users across an org. We also want to give the leadership of those organizations tools to to make the job of running a company like this easier and better. And so one of the things that I'm particularly proud of is, you know, we just rolled out this capability for official copilots. So one of the use cases you might think of with that is, you know, people across your org have tons of you know, IT-type questions. My Slack doesn't work today, or I can't log into my machine, or the printer's out of ink, or whatever. Anything like that. In those cases, you could have someone have to respond to every every one of those requests or you could build in a co-pilot and this is what we want people to use this official co-pilot for which is build your your IT assistant right into the tool so that people come here into one place and they They can use their own copilots for their own use cases, but they can also interact with the IT bot if they need that, or the HR bot if they have a question about... does what is my PTO policy look like or does it allow for this?

Josh Kriger: Yeah, I think it's really, it's a reframe of knowledge management that's pretty powerful, right? Because I think the way that people think is, how do I solve this one question? They don't think, let me review the full policy for X. And you can get to their bottom line need much faster with a prompting experience. It cuts a lot of time and energy.

Mark Denninson : That's absolutely right. And if the tool, we're not quite here yet, but if the tool knows who you are versus who I am, it can give us even better data. You don't have to, like you're saying, you don't have to have the whole policy and read between the lines of, well, this part of the policy doesn't apply to me, but this part does. the LLM or the Copilot can actually just give you that part that does apply to you.

Josh Kriger: Well, how are you using Copilot personally? Like, what are some of the fun things that you do with it? I'll share some of mine, too. Yeah, great.

Mark Denninson : As a product manager, I do a ton of A, documentation. B, like, just writing epics and user stories and bugs and things like that all the time. And so some of the stuff I'm using Copilots for every day is is I have a story writer, so it knows what kind of format that I like to write my stories in, it knows I like to use Gherkin in my acceptance criteria, it knows I like to add some notes, it knows that I have a I have a UI that exists in two different languages, so it gives me placeholder text in both languages that I can do that. They're saving hours. Absolutely saves hours and hours. And it allows me to focus on knowing my product and bringing the value that I bring, which is not writing all this stuff down. The value I bring is what could we be doing more of? What's a new idea? And what's great about these co-pilots is they can really help me brainstorm. It's not gonna come up with a new idea, but it's going to come up with, oh, did you think about this possible edge case over here? Or did you think about, how this might affect this other feature that we have because it already knows. I like feed it all this information about the product already. So it knows so much about what we have now that when I say, hey, I need a story for this, it actually knows how that relates to some of the other pieces.

Josh Kriger: Yeah, I mean, I can relate to that in terms of like we do events. It helps us come up with ideas for creative accoutrements to our events and programming ideas. And when we're interviewing folks like yourself, you know, it has some ideas for questions and it's a guide, right? I think, but it allows me to be at my maximum human creativity level, which is what I think everyone's looking for in life is to get to that state of being truly as creative as humanly possible. and not worrying about the minutia that doesn't sort of serve their ultimate sort of purpose for that objective. Right? Absolutely right. Yes. Makes a lot of sense. So you sort of danced with my last question for the interview, but we'll go into it now. So at the end of the day, your job is pushing innovation forward for this product, but ultimately sort of as a catalyst of innovation for enterprises, right? Sure. AI is moving so fast. You probably subscribe to these blogs and newsletters and you're learning about the new tools. How do you stay one step ahead of everyone else building tools like you and sort of ensure that innovation is sort of at your fingertips at all times?

Mark Denninson : Well, quite frankly, I've got a special weapon, which is the team that we have around this product. I don't know even how many people it is. It feels like it's hundreds, and it's absolutely not. Like the Matrix, they just clone themselves. Exactly. We have a lot of Matrix theme going on at Fuel. But I will say, one of the best ways of keeping up is everyone is so energized within the system of FuelX from people in leadership to people on the teams building the thing, coding it every day. Everyone's so energized by all the innovation that's happening around us and inside of us that we are sharing news releases and like did you see that the Anthropic just released this cool new thing or did you see that Light LLM has has a new feature out here or how this company's doing rag in a new and innovative way and so that kind of stuff I think, takes what can feel, to me, does feel very overwhelming. There is no shortage of AI news and AI thought pieces out there.

Josh Kriger: And you could be trying to integrate everything at all times and never sleep, right?

Mark Denninson : Yeah. Right. And so what's great is that the team, you know, the team helps kind of cut through that noise. And we all sort of help each other by saying, well, does this make sense for Fuel IX? Like, how do we take advantage of something like this? Is this something we can use? Is this something we can build on our own or do better. Um, uh, and that's the, that's the great kind of, uh, part of this. And you couple that with, you know, a co-pilot tool that can help you, like I was saying, help you just brainstorm things, um, left and right. I mean, there's, like you're saying it, it saves me hours and hours of of time, but also helps me leap forward in terms of what I can think of bringing to the table, bringing to this program.

Josh Kriger: So I promised you I would share a few of my things. I'm an avid traveler. I travel a lot for this company and personally. I've gotten to know the types of places I like to stay, the types of food I like, the types of experiences I like. So I have various prompts I use for any new location. Hey, I've got 12 hours to kill before I'm go, go, go. What are the best restaurants that are healthy but tasty? What are touristy things I can do in less than an hour? Give me a walking route to all these destinations that leaves me time to hit the sauna in the evening. It'll literally just plan my itinerary for the day. That saves me an hour of on-the-ground time. So that's one fun thing that I like to do.

Mark Denninson : I love that. And I love, you know, you can sort of see how that evolves and you could couple that with bringing in maybe your agenda from your calendar and saying, OK, I'm going to be here in this, not just in this city, but in this particular building. And what's going to be within a walking distance of that? And, you know, what's going to be open during that period? I think that's a great use case.

Josh Kriger: Yeah. And I think, you know, enterprises can benefit from that too, if they're doing like summits or conferences or not. I mean, there's executives that are traveling around. I mean, you know, all this sort of improves life, right? And improves productivity at the same time. You know, I'm a lot happier if I'm eating good food and enjoying the short burst of time when I'm not working. So it's a win-win for everyone. Well, this is great. Thank you so much for hanging out with me on the Edge of Show. And if folks want to learn more about your product, where should they go?

Mark Denninson : Fuelix.ai is the place to go. It's got everything right there, and it's got information about all the other products that we have, not just co-pilots. We have Fortify and Agent Trainer and all sorts of stuff. So it's really exciting.

Josh Kriger: I want to check it out.

Mark Denninson : Thanks, Mark. This was fun. Thanks so much.

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