Keet Wants to Be the Property Manager That Never Sleeps and Landlords Everywhere Should Pay Attention

The Macro: Property Management Is Stuck in the Voicemail Era

I spent a summer working at a property management company during college and I can tell you from direct experience that the industry runs on chaos. A tenant calls about a broken dishwasher. The property manager writes it on a sticky note. They call three plumbers to get quotes. Two do not answer. The third can come next Thursday. The tenant calls back asking for an update. The property manager checks their sticky note, realizes they forgot to follow up with the plumber who did not answer, calls again, gets voicemail again. Meanwhile, another tenant is emailing about a lease renewal, a prospective renter wants to schedule a showing, and the owner of the building wants the monthly financial report that was due yesterday.

This is not a caricature. This is Tuesday for most property managers in America. The industry manages over $4 trillion in residential real estate, and the majority of that portfolio is managed by small to mid-size firms using some combination of email, phone calls, spreadsheets, and legacy software that looks like it was designed in 2004 (because it was).

The property management software market is not empty. AppFolio, Buildium, Yardi, and RentManager are established players with significant market share. But these platforms are primarily record-keeping systems. They help you track leases, collect rent, and generate reports. They do not do the actual work of property management: responding to tenant requests, coordinating vendors, qualifying leads, scheduling showings, following up on maintenance tickets. That work still falls entirely on humans.

The opportunity for AI in property management is not replacing the software. It is replacing the labor. A property manager at a mid-size firm might spend 60 percent of their day on communication (responding to tenants, coordinating with vendors, answering prospective renters’ questions) and only 40 percent on decisions that actually require human judgment. If AI can handle the 60 percent, each property manager can manage two or three times as many units.

The Micro: An AI That Actually Responds to Tenants at 11 PM

Zack Ashen and Tommy Tsai cofounded Keet and brought it through Y Combinator. Both studied computer science at Cornell, and the team is small and focused.

The product addresses the three biggest time sinks in property management: maintenance coordination, leasing, and tenant communication. For maintenance, Keet handles the entire workflow from initial tenant request through vendor coordination to completion confirmation. When a tenant reports a problem, Keet triages the issue, determines urgency, contacts the appropriate vendor, schedules the repair, and keeps the tenant updated throughout the process. For a property manager handling 200 units, this alone could save 15 to 20 hours per week.

The leasing automation is equally valuable. Prospective renters have questions that are repetitive and time-sensitive. What is the monthly rent? Is parking included? Can I have a dog? When can I schedule a showing? These questions come in at all hours, and every hour of delay reduces the likelihood of converting that lead into a signed lease. Keet responds immediately, answers from the property’s specific details, and schedules showings without human involvement.

Tenant communication is the connective tissue. Rent reminders, lease renewal notices, building announcements, noise complaints, package notifications. The sheer volume of communication in property management is staggering, and most of it follows predictable patterns that AI handles well.

The competitive landscape in AI property management is heating up. EliseAI raised over $100 million to automate leasing and resident communication for large multifamily operators. Funnel Leasing focuses on the leasing funnel specifically. Quext and Anyone Home offer AI-powered answering services for property managers. But most of these target enterprise-scale operators with 5,000 or more units. The small and mid-size property manager running 50 to 500 units is underserved. They cannot afford a $50,000 per year enterprise platform, but they desperately need automation.

Keet’s positioning as a comprehensive AI property manager (not just a leasing chatbot or a maintenance tracker) gives it a broader value proposition. If it can handle maintenance, leasing, and communication in one product, that is three separate tools replaced by one. For a property manager evaluating software, consolidation is extremely attractive.

The security model is worth noting. Keet states that no data is stored on their servers and credentials are never retained. For an industry that handles sensitive personal information (Social Security numbers on lease applications, bank details for rent payments, and personal communication between tenants and management), data handling is a legitimate concern.

The Verdict

Property management is one of those industries that AI was made for. The work is repetitive, communication-heavy, time-sensitive, and follows clear patterns. The existing software handles record-keeping but not operations. The labor market for property managers is tight. The math works.

At 30 days, I want to see tenant satisfaction scores at properties using Keet versus properties managed traditionally. If tenants are getting faster responses and better follow-through on maintenance requests, the product is working. At 60 days, the question is vendor coordination. Getting a plumber to show up on time is a human skill that involves persistence, relationship management, and sometimes creative persuasion. Can AI handle that? At 90 days, I want to see whether property managers are taking on more units because Keet freed up their capacity. That is the ultimate proof of value: not just saving time, but enabling growth.

The property management industry is ripe for this exact product. Every property manager I have ever talked to says the same thing: they love the work of improving buildings and helping residents, and they hate the operational overhead that consumes most of their day. If Keet can absorb that overhead, it will find a massive and very willing customer base.