Station A and the Clean Energy Marketplace Buyers Needed

Episode Info

The clean energy transition has a strange problem: the technology works, and the economics work, but deployment doesn’t. Solar, storage, EV charging, pencil out on hundreds of thousands of buildings across the country.

And yet adoption is stuck at a tiny fraction of what’s possible. Not because the economics don’t work, but because the process does: slow proposals, opaque pricing, and a market that still behaves as if every project is bespoke.

Kevin Berkemeyer is trying to change that. He’s the CEO and co-founder of Station A, a marketplace built to make clean energy decisions instant, data-driven, and transparent. Instead of months of back-and-forth, Station A starts with intelligence: what makes financial sense, where, and why. And then it brings real competition to the table.

In this episode, we talk about why deployment lags so far behind potential, what Station A’s growing dataset reveals about the industry, and how rethinking the process, not technology, might be the key to unlocking the next chapter of clean energy in the US.

Interview with Kevin

Dunja Jovanovic: For readers meeting you for the first time, can you introduce yourself and the work you’re focused on today?
Kevin Berkemeyer: My name is Kevin Berkemeyer, and I’m one of the founders and the CEO of Station A, a clean energy marketplace built to make energy transactions dramatically more efficient, more scalable, and more cost-effective. Our aim is simple but ambitious: to become the leading clean energy marketplace, originating more projects than any other platform by bringing clarity, transparency, and scale to a market that traditionally moves slowly and manually.

DJ: What sparked the idea that eventually became Station A?
KB: My background is in solar and energy storage project development. I spent years sourcing good sites, developing projects, navigating incentives, and learning firsthand how fragmented the industry is. My co-founders came from building science and large-scale modeling. We each knew a different part of the problem, and when we came together, it was clear the industry kept repeating the same mistake: everyone sold point solutions, each delivered with its own pitch deck, assumptions, and tools. It created slow, expensive, and highly manual experiences for buyers. We believed the whole system could be flipped. Instead of starting with a pitch, we could start with intelligence: data-driven recommendations delivered instantly, simply from an address. From there, you could unify the entire workflow and address the industry's primary barrier: scalability.

DJ: Would you say scalability is the central problem you set out to solve in the clean energy space?
KB: Absolutely. The U.S. has deployed clean energy in only about five percent of viable buildings. That number is shockingly low, given that at least half a million sites are already financially viable for clean energy projects, representing nearly $300 billion in capital that would deliver positive returns to owners. We’re not lacking technology; we’re lacking a scalable way to identify the right projects and execute them efficiently. That’s the bottleneck we’re addressing.

DJ: You’ve emphasized from the start that Station A leads with financial performance rather than sustainability messaging. Why was that important?
KB: Businesses make decisions based on value. Financial fundamentals guide sustainability matters, but most organizations focus on lowering operating expenses, increasing net operating income, and managing risk. Clean energy can deliver all of that—and, as a bonus, it’s sustainable. But to unlock the market at scale, you have to begin with economics, not virtue. If the financial case is compelling, adoption follows naturally.

DJ: How did partners react to that approach early on? Did you face skepticism?
KB: Customers immediately appreciated having a data-driven, agnostic view of their options. Interestingly, our earliest skepticism actually came from investors, not buyers. Investors told us the status quo would never change, that marketplaces couldn’t work in this sector, that the process was too entrenched. Yet the market told us something different. We began as a data company selling insights to providers. Soon, building owners started approaching us to evaluate their portfolios. Then they asked us to recommend providers. That’s when the marketplace emerges, not from our pitch deck, but from customer pull. Today we’ve listed over 300 megawatts of projects—over half a billion dollars in project value—and work with some of the largest corporations in the world. Each step has disproved the early skepticism.

DJ: You use mapping and data modeling to analyze buildings. How does that help owners make financial decisions, and what were they struggling with before?
KB: Traditionally, a provider comes in with a menu of options and asks the customer what they’re interested in. But building owners aren’t experts—that’s why they’re talking to providers in the first place. Then the provider asks for data, spends months analyzing it, and finally returns with a proposal. We removed that entire cycle. We gathered every input needed to model a project: bill estimates, roof geometry, building type, incentives, shading data, and cost trends. Then we automated the analysis so that, in the very first meeting, a building owner receives a clear, data-backed recommendation on whether solar, storage, EV charging, or other solutions make financial sense. What once took months now takes seconds.

DJ: Early on, what did your sales experience teach you about the market?
KB: First, that listening is everything. Customer discovery is not optional. You cannot build something this ambitious in a vacuum. We’ve made experimentation a core part of our culture: test, learn, iterate, repeat. We also learned the importance of conviction. Once we identified a clear product-market fit, meaning customers consistently wanted what we were offering, and we could sell it repeatedly, we accelerated. But getting to that point required discipline, patience, and a willingness to adapt.

DJ: You’ve said Station A “de-risks” outcomes for customers. What does de-risking look like in practice?
KB: It means eliminating surprises. We run a structured, transparent process that brings every critical detail to light upfront—from a provider’s execution plan to contingencies to cost assumptions. We're now surveying both buyers and providers after project completion to understand where change orders occurred, where schedules slipped, and why. That feedback helps us refine our upfront evaluation and identify providers with reliable performance records. Ultimately, de-risking means delivering predictable, transparent results, not wishful thinking.

DJ: What has customer feedback looked like so far?
KB: Very strong. Many come to us after receiving proposals from providers, wishing they’d found us sooner. Yet even then, when they run their projects through our marketplace, we consistently deliver more and better bids. On average, our bids are about 20 percent lower than what they already had in hand, and from highly reputable providers. One of our core values is “show, don’t tell.” When customers see the data side by side, they immediately understand why this model works, and they come back.

DJ: There’s an ongoing debate in the clean energy sector about the role of incentives. How do you see incentives shaping behavior?
KB: The future is most exciting when we no longer rely on incentives—and we’re trending in that direction. Electricity costs are rising across almost every U.S. state. The fundamentals alone increasingly make clean energy economically compelling. At the same time, we’re working to reduce soft costs—often 35–50 percent of total project costs—so that project economics work even without policy support. That’s where true market transformation happens.

DJ: Station A has built a structured dataset on project pricing and provider performance. How does that create a flywheel effect?
KB: Everything we collect: costs, component choices, timelines, provider performance, feeds back into our models. For example, if we’ve run dozens of transactions in Arizona, our recommendations in Arizona become sharper: more accurate economics, clearer execution risks, better provider matches. It’s a compounding loop in which each project improves the next.

DJ: What have you learned from your data that surprised even you?
KB: Bid spreads are enormous, often 50 percent from the lowest to the highest. On a typical project, that’s a million-dollar swing. Execution timelines vary wildly, too. Those gaps reflect differences in expertise, contingency assumptions, and, at times, a lack of transparency. It underscores why a clear, apples-to-apples comparison is essential for buyers.

DJ: What’s next for Station A?
KB: We’re expanding in two directions. Horizontally, we’re enhancing the transaction process, supporting contract negotiations, standardizing terms, and broadening the services that help customers avoid downstream surprises. Vertically, we’re expanding the solution set: behind-the-meter solar and storage, front-of-the-meter projects, EV charging, community solar subscriptions, and more. The customer’s goal isn’t to “do solar,” it’s to reduce operating expenses or increase asset value. Our role is to be an agnostic partner who helps them achieve that outcome with the right mix of solutions.