Inside Real Estate is doubling down on its push into artificial intelligence with the launch of Streams, a new mobile app designed to help agents act faster on high-intent leads and close more business while on the go.
The Murray, Utah-based company announced Tuesday that the app will roll out first to users of its BoldTrail platform, with BoomTown users and other integrations expected to follow as part of a broader AI expansion strategy.
At its core, Streams is built to solve a familiar problem in modern real estate workflows: the lag between when a consumer signals intent and when an agent actually responds.
Catching buyers before they move on
Buyer activity, from favoriting listings to requesting showings, often gets buried in CRM dashboards or overlooked entirely. By the time agents surface those signals, the opportunity may already be gone.
Streams aims to eliminate that delay by pushing real-time insights directly to agents’ phones, highlighting which leads are “heating up,” what requires immediate follow-up, and what actions to take next.
“Our goal with Streams was to remove the gap between when a lead signals intent and when an agent can respond,” said Julia Laurin, Chief Product Officer at Inside Real Estate. “By combining real-time signals with an AI assistant in a mobile-first experience, we’re helping agents stay proactive wherever their day takes them.”
The company says early beta users are already seeing measurable gains, including three times more conversations and productivity increases of up to 250 percent.
‘Flash without impact doesn’t mean much’
The launch comes at a time when AI has become (obviously) a dominant theme across proptech, yet many agents and brokers have struggled to translate it into tangible business results. Inside Real Estate CEO Joe Skousen framed Streams as a response to that gap between promise and performance.
“AI is everywhere in the conversation right now, but flash without impact doesn’t mean much to the real estate professionals we serve,” Skousen said.
Skousen said the difference between AI that sounds impressive and AI that actually closes deals comes down to two things.
“First, the intelligence behind it — AI is only as powerful as the breadth, depth, and quality of its inputs,” Skousen continued. “We’ve spent decades building what no one else in this space has: tens of millions of leads, hundreds of millions of behavioral signals, trillions of data points, all analyzed and optimized to drive outcomes.”
He added that the second factor was the ability to act on that intelligence effortlessly. “Not just a simpler interface, but the power of conversation, meeting agents where they are, in the moment that matters,” he said.
Embedding AI directly into daily workflows
Rather than positioning Streams as a standalone product, Inside Real Estate is framing it as the mobile execution layer of its broader “AI Advantage” ecosystem.
The app connects to tools like HomeSearch AI, Learning Alerts, and Concierge AI, aggregating signals from across the platform and translating them into actionable prompts for agents in real time.
The approach reflects a broader shift in proptech: moving away from adding more dashboards and toward embedding AI directly into daily workflows. The company says that beta participants using the app reported that the immediacy of those signals is already translating into deals.
Meeting agents where they are
For years, real estate technology has focused on building more tools to improve productivity. Inside Real Estate is betting that the next phase will be less about adding features and more about orchestrating intelligence across existing systems.
Streams reflects that thesis: an AI layer designed to work across platforms, rather than requiring agents to change how they operate.
“Agents should not have to change how they work to benefit from AI,” the company said in its announcement. “The technology should meet them where they are.”
With nearly 400,000 agents and brokerages already using its software ecosystem, Inside Real Estate is positioning Streams as the first step in a broader push to turn AI from a back-end capability into a front-line productivity driver.
