Zuma's Shiv Gettu on AI-Driven Property Management Solutions

Written by:

Date:

11 Mar 2025

When the COVID-19 pandemic hit in early 2020, Shiv Gettu and his co-founder Kendrick Bradley watched their thriving short-term rental business collapse virtually overnight. Within five days, they went from being “wildly profitable” to losing $100,000 a month. With landlords threatening legal action and no travelers booking their properties, they faced a business catastrophe.

“We had all these rent contracts. We had to pay these rent contracts, and it was just a nightmare of a situation,” Gettu recalls. “Landlords barking down our door. People threatening to sue us, trying to rent properties on Airbnb for dollars, and nobody was buying because we were in the middle of a global pandemic.”

This crisis moment became the catalyst for Zuma, now one of the leading AI-driven property management technology companies in the multifamily housing sector. The company’s journey from desperate pivot to industry pioneer offers valuable lessons for real estate professionals navigating market disruptions and technological advancement.

From SpaceX to Property Management

Gettu’s path to real estate technology wasn’t traditional. While his great-great-grandfather had received land from British colonizers in South India as payment for medical services, the family’s real estate holdings had diminished over generations. After college, Gettu was determined to build financial security through real estate investment, but lacked capital.

In 2018, Gettu and Bradley, friends since college, devised a creative solution: they would lease apartments from landlords, convert them to short-term rentals, and profit from the margin. Bradley even left his position at SpaceX to become a leasing agent at a property management company, creating an inside track to available units.

“My co-founder went from working at SpaceX to becoming a leasing agent,” Gettu explains. “We knew that we wanted to build this business, and we thought that the best way to siphon off properties from property management companies was to actually become a leasing agent.”

Their hustle caught the attention of the property management company’s owner, who was impressed by what these twenty-something entrepreneurs were accomplishing. By late 2019, he invested $500,000 in seed capital, allowing them to quit their jobs and expand their business.

Just months later, COVID-19 wiped everything out.

Crisis-Driven Innovation

Facing financial ruin, the founders quickly pivoted from short-term to long-term rentals. But without Airbnb’s platform infrastructure, they found themselves drowning in operational chaos—scheduling tours, answering prospect questions, and managing leads.

“We were drowning in weeds,” says Gettu. “We had all these inbound renter leads coming in. We had to schedule all these appointments and tours, and it was just a nightmare. It was just so chaotic.”

In what Gettu describes as “desperation and necessity for survival,” they built an AI leasing agent to handle these workflows. Within two months, they went from hemorrhaging cash to breaking even. The business stabilized, but they realized they had created something potentially more valuable than their original venture.

When their investor noted that his own portfolio could benefit from their automated leasing solution, Zuma’s current business model was born. By early 2021—before ChatGPT and the mainstream AI boom—they had launched their AI leasing assistant, Kelsey, and secured seven-figure funding.

Enterprise-Grade AI for Property Management

Today, Zuma serves institutional property management companies managing portfolios ranging from 1,000 to hundreds of thousands of units. Their flagship product, the AI leasing assistant Kelsey, significantly improves operational efficiency and conversion metrics.

“The core problem we’re solving is, in every institutional management company, you have labor that is currently being done by humans, that should be done by AI and should be done by technology,” Gettu explains. “We want to build that technology to help run these businesses more effectively and enable humans to focus on energizing work.”

The results have been impressive. Properties using Zuma’s technology see median response times to prospect inquiries drop from over 100 hours to just two minutes, with 95% of leads receiving responses within three minutes. Leasing agents find their calendars filled with qualified tours, while ownership groups receive actionable feedback insights through sentiment analysis.

A key technical differentiator is Zuma’s deep integration with property management systems like RealPage, Yardi, and Entrata. Rather than simply providing a user interface layer, Zuma’s AI actually operates within these systems.

“The way you can think about it is you have basically an AI assistant that lives in your CRM, that lives in your property management software, and is taking action and moving things the same way the human would,” says Gettu. “What that requires is very deep integration with these systems, so that whatever a human is doing in that system we’re doing through technology.”

Product-Market Fit: Mining Your Way Out

When asked about lessons learned in achieving product-market fit, Gettu offers a striking metaphor that should resonate with real estate entrepreneurs and technologists alike.

“The way I view product market fit is a miner that’s in a cave and needs to take his way out,” he explains. “There’s no room to think outside. You’re stuck. You see one box in front of you, and your goal is to mine yourself out.”

He advises founders to “narrow the aperture so small and so tight, where you see one small problem and all you try to do is solve that problem as tightly as possible for 100 people and make them love that solution in the lowest common denominator as much as possible.”

This focused approach runs counter to the urge many entrepreneurs feel to address multiple problems simultaneously or chase larger markets immediately. Gettu notes that while investors might lack vision for how a narrowly-defined solution can evolve, the strongest businesses typically start with tight focus.

“You look at Amazon starting as a book company, right? The reality is the best businesses start with a really narrow aperture, because otherwise you can’t really—it’s very complicated to build a business that does a lot very quickly to reach product-market fit.”

The Future: Beyond Point Solutions

Looking ahead, Zuma aims to address the entire resident lifecycle, from initial inquiry through move-out, by identifying human-intensive workflows that can be automated with AI. They see particular opportunity in maintenance coordination, where AI can potentially replace the human labor of dispatching service personnel and tracking work orders.

Perhaps most ambitiously, Gettu envisions Zuma becoming “the de facto intelligence player” that helps property management companies make sense of their fragmented data landscape. By connecting information currently siloed in different systems, Zuma could enable predictive capabilities like identifying residents likely to renew their leases and suggesting proactive retention strategies.

When asked about differentiation in an increasingly crowded AI landscape, Gettu offers a thought-provoking perspective that challenges conventional wisdom about competitive advantages.

“I don’t think there’s real differentiation anywhere,” he says. “I really think the only differentiation that will last is brand and building brand and using brand as a moat. But I think ultimately it comes down to execution. The company that’s going to go deepest in the vertical and continue to build and become the de facto solution is the one that’s going to win.”

His insight reflects the reality that technological advantages can be fleeting in today’s fast-moving AI environment. He cites the recent emergence of DeepSeek as an example of how quickly competitive landscapes can shift, even for companies like OpenAI that seemed untouchable.

For property managers assessing the proptech landscape, Gettu’s philosophy suggests that when evaluating technology partners, long-term commitment to the industry and consistent execution may ultimately matter more than any particular feature set or AI capability.

As multifamily housing continues its technological evolution, Zuma’s story illustrates how crisis-inspired innovations, guided by disciplined focus and deep industry understanding, can create solutions that fundamentally improve property management operations. By automating routine tasks and freeing human talent for higher-value activities, companies like Zuma are helping to shape a more efficient, responsive, and ultimately more human-centered approach for the industry.