The first thing Spencer Gray wants you to understand is that he is not working less.
Sitting in his Indianapolis office, the founder of Gray Capital told listeners of The Gray Report podcast that despite the hype around artificial intelligence and automation, his days are longer and more crowded than ever. The office, he noted, has never been fuller. There are more people on payroll, more desks occupied, more projects in motion. And yet, inside this thoroughly human, analog setting, Gray and his team are quietly gutting as much as a million dollars a year in software costs across their portfolio — by leaning harder into AI, not away from it.
This is the paradox at the heart of Gray Capital's experiment: build more technology, hire more people and spend less on third‑party software, all at the same time.
Rethinking The Real Estate Tech Stack
Over the past two years, the multifamily investment firm has been re‑architecting the digital plumbing of its business. Where many middle‑market real estate platforms subscribe to a patchwork of off‑the‑shelf products, Gray and his partners have been systematically identifying categories of spend where the software was too clunky, too generic or simply too expensive for the value delivered.
Instead of shopping for a better license, they started asking a different question: could they build something themselves — cheaper, faster and more aligned with how Gray Capital actually works?
Gray described the outcome of that exercise in unusually blunt financial terms. The team, he said, has identified hundreds of thousands of dollars, up to a million dollars a year, in software costs that can be eliminated over time.
The number is portfolio‑wide, spread across property‑level tools, corporate systems and niche platforms that crept into daily workflows during the long expansion cycle when money was cheap and software was sold as a cure‑all for operational pain.
In isolation, that sounds like a standard efficiency play: cut licenses, save money. What makes Gray Capital's approach notable is what happens next. Instead of dropping those savings to the bottom line or using them as an excuse to trim staff, the firm is redirecting them toward building and maintaining its own AI‑enabled tools and toward hiring.
From Generic Platforms To Custom Tools
The internal tool‑building started as a skunk‑works effort. Gray and a small group inside the firm began experimenting with ways to stitch together AI models, lightweight code and existing data sources into systems that could actually move the needle. Underwriting templates became more dynamic. Data analysis pipelines became more automated. Investor‑facing outputs became richer and faster to produce. New services emerged that would have been hard to justify if they depended on yet another subscription.
On the podcast, Gray likened the shift from off‑the‑shelf platforms to homegrown tools to swapping out a generic insole for one made specifically for your foot. The old systems required the firm to adapt to the software — to bend investment processes and asset‑management practices around the constraints of products built for the broadest possible market.
The new tools, by contrast, are being designed to wrap around Gray Capital's own workflows, idiosyncrasies and all. They model the way the firm already thinks about risk, markets and portfolios, then scale that thinking.
AI is doing more here than powering a chat window. Inside Gray Capital, it is embedded in what Gray calls "agentic systems" — clusters of AI agents and coding tools that can design workflows, write and refactor code and orchestrate tasks across the firm's data landscape.
Some of these agents run on local machines, but much of the heavy lifting happens on remote compute resources rented from cloud providers as needed. They function as always‑on digital staff, quietly writing scripts, crunching numbers and wiring together internal applications in the background.
More Work, Not Fewer People
The irony is that all this automation has not produced a leaner headcount. It has created more work.
As underwriting cycles shorten and analysis becomes deeper, the firm can evaluate more deals and slice its existing portfolio in new ways. As reporting tools improve, investors come to expect more frequent, more tailored insights. As resident‑facing technology gets smarter, the range of possible services expands. Each new internal system introduces maintenance, iteration, and support demands. The stack is lighter on outside vendors, but heavier on internal complexity.
Gray's response has been to dive into that complexity rather than pull back from it. On the podcast, he revealed that Gray Capital is bringing on a full‑time, full‑stack software engineer to own this growing constellation of internal tools.
A few years ago, the idea of a dedicated engineer on staff would have felt aspirational for a firm of their size — something for a later stage. Today, it feels necessary. There is simply too much code, too many AI‑driven workflows and too many ideas on the whiteboard to treat software as a side project.
Crucially, that hire is not being justified in the abstract. It is being funded, in part, by the very software savings the firm has unlocked. Each license that goes away frees up budget to support an internal salary and further development.
The cost line that once flowed out of the company and into SaaS providers' revenue statements is being redirected toward proprietary intellectual property and in‑house expertise. That kind of substitution — vendor spend for owned capability — has very different long‑term implications than a simple cost cut.
Inside Gray Capital, the answer for now looks like this: fewer external software contracts, more internal code; fewer generic systems, more tailored ones; no reduction in staff, but a busier, more technically fluent team.
For commercial real estate investors scrutinizing a sponsor's operating platform in 2026, that combination — the willingness to tear apart the tech stack, the discipline to redirect savings into human capital, and the patience to build tools that truly fit the business — may prove as material as cap rates and rent rolls.
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