A growing number of proptech companies are racing to embed AI into everything from CRMs to marketing platforms. But one startup is taking a different approach: Instead of building another feature, it wants to sit on top of the entire stack.
BrokerBot is positioning itself as a brokerage-wide AI assistant designed to operate across systems, not just within a single system. CEO and Co-Founder Jerimiah Taylor says the goal is to create a tool that behaves less like a chatbot and more like a digital team member, able to answer questions, execute tasks, and coordinate transactions from start to finish.
The idea emerged from a familiar brokerage pain point: agents constantly asking brokers for guidance on contracts, compliance rules and edge-case scenarios buried in documentation. BrokerBot was initially designed to absorb that institutional knowledge and make it instantly accessible. But Taylor said the platform has quickly evolved beyond answering questions into executing multi-step workflows.
In one example, the system can read a real estate contract, extract key dates, generate calendar reminders, draft emails, input contacts into a CRM and flag missing information, all before a human reviews the file.
“That’s where this is going,” Taylor told Inman, referring to the future of AI in real estate. “The machine becomes the transaction coordinator.”
The rise of the “agent operating system”
Unlike many AI tools embedded within existing platforms, BrokerBot is designed to function independently and connect across systems. Taylor said the company is building integrations with tools like Google Calendar, Gmail, Outlook, Canva, Close and Follow Up Boss, allowing the assistant to move between workflows the way a human staffer would.
“What we’re seeing is everybody else has gone outside in,” he said. “We are building the most sophisticated standalone AI agent that will exist in this space.”
The company says it is already working with 240 brokerages and about 24,000 agents, and recently signed a national partnership with Keller Williams Realty International to integrate BrokerBot into its Command platform.
That positioning reflects a recent shift in proptech AI. Rather than relying on a single large language model or a single platform, many proptech companies — including Breezy and Homie — are now building “real estate agent operating systems” that combine multiple models, proprietary data and workflow integrations into one system.
Speed and simplicity drive adoption
BrokerBot uses an internal benchmarking system — dubbed “BrokerBench” — to evaluate how different AI models perform on real estate-specific tasks such as contract analysis and licensing exam questions.
Based on those results, the system can route tasks to whichever model performs best, rather than relying on a single general-purpose model for everything. Taylor said this is especially important in areas like contract extraction, where errors or omissions could carry real liability.
“Some models like ChatGPT miss a lot,” he said, noting that performance varies significantly depending on the complexity of the form.
The platform also builds a permissions-based knowledge system that blends brokerage documents, vetted web sources and user-specific context. That allows responses to adapt based on geography, MLS rules or brokerage policies without requiring agents to manually input that context every time.
While the backend architecture is complex, Taylor said the product’s success ultimately depends on simplicity at the user level. Real estate agents, he said, are less concerned with how the system works and more focused on whether it can deliver results instantly.
“What they care about is, can they ask it for a thing and get what they ask for in real time?” Taylor said.
As AI expands, so does scrutiny
As AI tools expand into more parts of the transaction, Taylor said regulatory considerations are becoming increasingly important.
This year, California became the first state to establish a clear standard for acceptable AI use in real estate marketing through Assembly Bill 723.
The law, which took effect Jan. 1, requires that any property images that have been “digitally altered” in an advertisement or promotional context be clearly disclosed, with the original, unedited version also made available. In practice, that means if a room is virtually staged, the listing must both label the image as altered and include the unstaged photo alongside it.
“What’s going to happen is now a lot of these companies building AI systems in real estate are going to need to call a hard timeout and build more robust guardrails,” Taylor said. That dynamic could shape the next phase of proptech AI, where compliance infrastructure becomes just as important as raw capability.
What Disneyland reveals about the future of agents
Rather than replacing agents, Taylor believes AI could push them into a more elevated, experience-driven role that resembles a high-touch concierge service. He frames the shift with an unexpected analogy: Disneyland.
Taylor points to Disney’s premium guided experience, where guests can pay thousands of dollars for a dedicated staff member to lead them through the park, skipping lines and tailoring the day in real time.
“They give you a guide, and they walk you around, take you to the front of every line,” Taylor explained. “I call it the ‘human fast pass.’ People pay for that experience because it’s an experience.”
As AI tools take over repetitive, rules-based tasks in real estate, the traditional responsibilities of agents are being unbundled. What remains, Taylor suggests, is the part of the job that tech still struggles to replicate: human perception, intuition and emotional intelligence.
“That person is curating your journey,” he said, referring to the guides at Disneyland. “They’re explaining things to you along the way. They’re watching what you’re doing and ordering you a churro when you look a little hungry.”
In real estate terms, that means anticipating client needs before they’re explicitly stated, reading subtle cues during showings or negotiations, and connecting insights that aren’t easily captured in data.
The implication is not just a shift in responsibilities, but a redefinition of value. In a world where AI can accelerate transactions and reduce friction, speed becomes less of a differentiator. Experience becomes the product.
“The really perceptive real estate agent has an opportunity to be a curator of an experience,” Taylor said, “and use the machine to their advantage so they can go significantly faster and spend more time on the experience versus the transaction.”
If Taylor’s vision of the future holds, the real estate agent of tomorrow may look less like a dealmaker and more like a guide — one who knows when to step in, what to say, and, occasionally, when to order the metaphorical churro.
