SMU: How would you explain in a sentence or two what Emanate does for a steel or industrial materials company today?

Kiara: Emanate builds AI agents that run the entire commercial side of industrial materials and steel companies. We handle everything coming into a sales inbox, help manage and grow existing accounts, and run outbound to win net-new accounts, all connected to a company’s existing systems of record, with or without human supervision. Essentially, the companies we work with are able to grow revenue autonomously without needing a human involved in every step.

SMU: Steel is at the center of the reindustrialization of the US and reshoring efforts. A lot of that focus is on new plants and facilities, but Emanate is focused on the commercial side. Can you say a little about how you see the unsolved problem being how these products actually get sold?

Kiara: What’s interesting is that every new factory, every chip fab, and every data center starts as a quote on a desk at a steel company. Before anything gets built, materials have to be specified, priced, quoted, sold, and moved. The commercial layer is really the bloodstream of the entire buildout, and it still runs on spreadsheets, emails, phone calls, and CRMs that are not as up to date as they should be.

We’ve dedicated an incredible amount of intelligence and complexity to improving that commercial layer. Almost nobody has really touched the selling side. The making only matters when what gets sold is sold well. That’s the unsolved half, and that’s the half we build for.

SMU: In that sales process, where do you see the biggest friction in the quote-to-order process, where Emanate is trying to make the biggest impact first?

Kiara: It’s really everything from when the quote comes in to how you sustain net-new quotes. A single request means matching specs, grades, checking inventory, and doing multiple checks before a quote actually goes out. Once it does go out, that’s revenue coming in the door.

But then, to maintain wallet share and make sure the customer keeps purchasing, you need to continue managing that account at a speed and precision that goes beyond one human. So the biggest friction we see is not just handling inbound quickly and effectively, but maintaining that momentum so you have continued revenue throughout the sales process after that initial inbound

SMU: For a steel company you’re working with, what does implementation look like in terms of incorporating this technology into their processes and workflows?

Kiara: We are platform-centric, but also forward-deployed, as many AI companies are right now when they’re driving real value. AI is different from SaaS. With SaaS, you’re buying a product. With AI, you’re purchasing outcomes.

That’s incredibly unique, but also incredibly exciting to a company, because you can anchor on what the agent can actually do: how many quotes it is processing, how many outbounds it is doing, and what net-new revenue sources it is unlocking. So when we deploy, we focus on integrating, customizing, and tracking ROI for every deployment, with as little friction as possible.

And the results are tangible. On the inbound quote side, anything that used to take two or three weeks, or even multiple days, can now be done in two to three minutes. You’re able to cover every single piece of inbound coming in. You’re able to reactivate dormant accounts at scale through automated nurturing.

SMU: A lot of readers may be familiar with AI mainly through platforms like ChatGPT or Claude. How would you describe the difference between those horizontal tools and a vertically built platform?

Kiara: That’s a great question. ChatGPT and Claude are incredible one-size-fits-all tools. But selling in this industry is not a language problem. It’s a knowledge and computation problem.

These products are deeply complex. You have technical specs, grades, processing requirements, and real mathematical decisions around how they’re priced, processed, and delivered. A horizontal AI tool can give you a plausible paragraph. It can’t tell you what’s on your floor, what it costs to process, what to charge with the right margins, which customers are at risk, how to expand those customers, or who sits on the buying committee in a procurement team.

Our agents hold that deep domain knowledge. We build that out for you based on the specifics in your ERP or CRM, and then we do the real computation at the same time. Every decision is connected to your live systems. That combination is why horizontal AI can’t replicate what we do.

SMU: Given the speed of innovation within AI, people talk about a kind of great level- ling, where other sectors can move as fast as software companies. How do you see that applying to steel service centers versus software companies?

Kiara: It’s an incredible point. For decades, a tech company in San Francisco could adopt new technology as fast as it came out, and that became its moat or advantage over, say, a service center in another part of the country. That was the real gap. It wasn’t ambition. It was access and engineering capacity.

Frontier AI changes that. We’re living in a time where the model today is as bad as it’s ever going to get. That’s wild, but it’s true. The models we’re interacting with now are only going to improve over the next month, six weeks, and beyond.

That means if you step up and use this technology now, you can get ahead in a way that has never really been possible before.

SMU: When you’re talking to clients, how do you describe the need to focus on building for growth rather than cost-cutting?

Kiara: I think most leaders in steel companies understand this deeply. When you adopt a new tool or technology, you have to focus on growth. Cost-cutting has a floor. Growth doesn’t.

A lot of enterprise AI enters the market framed as doing the same thing more cheaply. That’s shrinking ambition. What Emanate does is different. These companies don’t have a cost problem; they have a coverage problem.

Re-industrialization is happening. They don’t need to cut costs to become more relevant. On the revenue side, they can now cover all inbound demand effectively, maintain existing accounts, and find net-new accounts as quickly as possible. Cost-cutting has a limit. Growth is the real opportunity.

SMU: What are you most looking forward to discussing, or what do you encourage people to come to the summit to ask you about?

Kiara: What I’m most looking forward to discussing is this: if you are a C-suite leader at a steel company, how do you make your top-performing sales rep equivalent to your entire sales team?

If you want that, then you need to deploy Emanate on your commercial side, because it allows you to replicate your highest performer across the team. It also safeguards your company if those top performers leave, because you’ve built an institutional commercial layer that keeps growing. That’s how we think about it: protecting the company, growing the company, and augmenting the existing team.