Visitt Raises $22M Series B to Build a Single AI Interface for CRE Property Operations

Commercial real estate teams are entering a new phase of operational modernization, and Visitt’s latest funding milestone is a strong signal that “AI-native operations” is moving from buzzword to day-to-day reality in buildings. Visitt, an AI-native property operations platform focused on commercial real estate (CRE), has announced a $22 million Series B round led by Susquehanna Growth Equity, with continued participation from Vertex Ventures Israel, Anfield, and Sarona Ventures. For property owners, operators, and asset managers, the headline isn’t only the capital raised—it’s the product direction: Visitt is positioning itself as a single AI interface that sits inside core building workflows, bringing speed and clarity to teams that have historically been forced to juggle too many disconnected tools.

At the ai world organisation, we track funding and product innovation like this because it shows where AI is genuinely creating measurable operational outcomes, not just generating impressive demos. This is also the kind of practical, implementation-focused transformation that repeatedly surfaces in discussions across ai world organisation events and panels—especially as leaders plan their 2026 playbooks and prepare for the ai world summit and the broader ai world summit 2025 / 2026 conversation cycle. In that context, Visitt’s momentum provides a clear case study in how agentic workflows, automation, and predictive intelligence can be embedded directly into frontline operations without forcing property teams to re-learn everything from scratch.

The $22M round and what it signals for CRE ops

Visitt’s Series B was announced from New York on January 26, 2026, with Susquehanna Growth Equity leading the round and existing investors Vertex Ventures Israel, Anfield, and Sarona Ventures participating. This matters because growth-stage rounds in CRE software are increasingly being won by platforms that do more than store data—they actively help teams run buildings better through automation, intelligence, and tighter workflow execution. Visitt is explicitly framing its next stage around becoming the unified operational layer for property teams, which is a direct response to the “tool sprawl” problem many operators face today.

The company is also tying this funding announcement to sharp growth claims: Visitt says it now serves more than 150 customers and achieved more than 900% growth in managed square footage in 2025. That combination—rapid portfolio expansion plus a workflow-first product—is one reason this funding story is resonating across PropTech conversations. When adoption expands that quickly, it typically suggests the product is reducing friction in the field, not adding another dashboard that teams ignore after onboarding.

From an investor perspective, the narrative is built around a large “whitespace” opportunity in CRE operations and a belief that a best-in-class, AI-native platform can scale broadly across asset types. Susquehanna Growth Equity’s leadership has highlighted the platform’s focus on solving common CRE pain points and the potential to expand significantly as property teams standardize on unified systems rather than patchwork stacks. For operators, that investor thesis translates into a simple question: can a single interface actually replace multiple systems while improving response time, compliance discipline, tenant experience, and reporting quality? Visitt is betting that the answer is yes—if AI is embedded at the operational core rather than bolted on later.

As the ai world organisation continues to cover applied AI across industries, we see this funding round as another example of how operational AI is maturing: the winning products are the ones that sit closest to “work that must get done” every day. It’s also precisely why these themes show up repeatedly in ai conferences by ai world, where the focus is increasingly on deployment patterns, governance, workforce adoption, and repeatable ROI—not just model capabilities.

Why “single AI interface” is a big deal in building operations

CRE operations has a unique challenge: it is both highly physical and relentlessly time-sensitive. A single property can involve maintenance, vendor coordination, compliance work, tenant communication, preventive maintenance scheduling, access management, and a steady stream of exceptions that don’t fit neatly into templates. In many organizations, each of those functions can live in a different tool, in a different spreadsheet, or in someone’s inbox, creating gaps that are costly but hard to quantify.

Visitt’s core positioning is that legacy CRE systems were built for another era and no longer meet modern expectations for operational excellence and tenant experience. The company’s leadership argues that operators need faster decision-making, clearer visibility, and real outcomes delivered through one interface where AI isn’t optional—it is built into the platform’s operational core. In practice, this “single interface” idea is less about having one screen and more about having one operating logic: one place where work is created, assigned, tracked, escalated, and learned from over time.

In an operations environment, AI becomes most valuable when it reduces coordination overhead. That can mean automatically classifying a request, routing it to the right person, identifying missing information, prompting best-practice steps, and ensuring the loop closes with documentation—without the team needing to chase updates across channels. When platforms can do that consistently, they become less like software and more like an operational teammate, especially for lean teams managing large footprints.

This is also where the “AI-native” claim becomes important. Visitt is describing its product as a unified platform designed from day one to solve day-to-day building operations challenges, rather than a legacy product retrofitted with AI features. In many industries, retrofits can work; in building operations, retrofits often fail because the workflow reality is messy, repetitive, and full of edge cases. The systems that succeed are usually the ones designed around what technicians, property managers, and onsite teams actually do, minute by minute.

From the ai world organisation lens, the most interesting aspect of this strategy is how it mirrors what we’re seeing across other operational domains like manufacturing, logistics, and service delivery: “AI interface + agents + automation” is replacing “point solutions + manual coordination.” That shift is central to many sessions across ai world organisation events, where organizations are actively trying to standardize processes and make outcomes repeatable at scale—especially as the ecosystem gears up for the ai world summit and the next wave of enterprise AI adoption stories often associated with ai world summit 2025 / 2026 planning cycles.

What Visitt’s platform is built to unify (and why that matters)

Visitt describes its platform as an all-in-one environment that brings together workflows that often live in disconnected CRE systems. The company specifically points to functions such as work orders, compliance, predictive maintenance, tenant communications, equipment lifespan tracking, security, amenities, and finance. That list is important because it spans both “reactive” work (like requests and incidents) and “proactive” work (like preventive maintenance and lifecycle planning), which is where ROI and tenant satisfaction often compound over time.

Another notable part of Visitt’s story is the data foundation. Visitt says its workflows are supported by millions of operational data points, paired with continuous feedback loops from onsite property teams. In a domain like CRE operations, data quality and feedback loops are often the difference between automation that feels magical and automation that feels risky. If a platform is fed inconsistent inputs, the AI layer can amplify noise; if the platform is designed to tighten data capture during work execution, the AI layer becomes more trustworthy as usage grows.

Visitt’s leadership team is also emphasizing a “built with operators, in live workflows” approach. The company says the platform was built around real-world workflows informed by live building operations, with operators across multiple property types including office, industrial, data center, multifamily, and retail. That matters because operational maturity varies across asset classes; a platform that can adapt to different property realities without breaking consistency is more likely to become the standard system of record across a portfolio.

In day-to-day terms, what does unification actually change? It reduces the number of handoffs needed to solve a tenant issue, lowers the chance that compliance documentation is missing, and makes it easier to run consistent preventive maintenance across sites. It can also improve training and continuity: when workflows are captured in one platform, new team members learn faster, and performance can be compared across buildings using common definitions rather than improvised reporting.

This operational clarity is one of the most recurring themes we hear in the global AI community, and it’s exactly the kind of applied transformation that ai conferences by ai world aim to surface through real deployment stories and case-based discussions. At the ai world organisation, we focus on these “operations-first” AI deployments because they tend to create durable value: improvements that persist after the novelty wears off, and systems that get stronger as teams use them more.

Growth, investor confidence, and the people behind the product

Visitt is led by a founding team that includes CEO Itay Oren, CTO Idan Wender, and CPO Jonathan Kroll. In its funding announcement, the company connects product direction to leadership philosophy: it positions itself as a partner to customers, building alongside property teams and staying grounded in real operational needs rather than abstract feature roadmaps. That approach aligns with a broader industry lesson: in operational software, “being close to the floor” matters because every small friction point can become a daily tax on performance.

Susquehanna Growth Equity’s leadership has publicly expressed confidence in Visitt’s team and product, describing it as a best-in-class platform built through focused commitment to solving common CRE industry issues. The firm also highlights the scale opportunity and indicates it is eager to support the company as it expands. Additionally, SGE has pointed to Visitt’s user-friendly AI workflows and their role in improving building operations and tenant experience, ultimately supporting measurable ROI for owners and operators.

While it’s easy to treat investor quotes as routine, they do point to an important reality: the CRE operations category is shifting from “systems that record work” to “systems that help complete work.” When investors see a platform that makes frontline teams faster and improves tenant outcomes, they are often betting on network effects and scaling advantages: more buildings mean more operational patterns learned; more patterns learned means better automation; better automation encourages broader adoption across portfolios.

Visitt’s reported traction—over 150 customers and over 900% growth in managed square footage in 2025—also suggests that this category is being adopted not only by innovators, but by operators who are actively replacing older tools. That replacement behavior is meaningful because it’s harder than adding “one more tool.” Replacement only happens when the perceived cost of switching is outweighed by the operational upside and when teams believe the platform can handle the messy realities of building ops.

From the ai world organisation perspective, this is exactly why we spotlight stories like this in our editorial coverage and discussions at ai world organisation events. When an AI platform is tied to real operational throughput—faster closeouts, fewer missed steps, better documentation, and improved tenant responsiveness—it becomes a practical blueprint that leaders can learn from and debate at the ai world summit, especially as the community looks toward ai world summit 2025 / 2026 themes around agentic AI, automation, and measurable enterprise value.

What Visitt says comes next: agents, predictive intelligence, and automation

Visitt’s roadmap focus is clear: it plans to expand the “single AI interface” within the workflows teams already use daily, while introducing new AI agents, deeper predictive intelligence, and more automation across core property workflows. The company notes it will build on existing capabilities that include work order intelligence, an AI agent for certificate of insurance management, and multilingual communication tools. It also says it will introduce new AI agents that reduce manual work, improve predictive intelligence, scale customer experience teams to ensure customer success, and continue advancing its proprietary onboarding technology.

In practical terms, this direction suggests a shift from “AI assists users” toward “AI executes tasks end-to-end within guardrails.” In operations-heavy environments, that’s the difference between having AI that drafts suggestions and having AI that actually moves work forward: collecting missing inputs, validating compliance, prompting follow-ups, escalating when needed, and learning from outcomes. Over time, the compounding effect can be substantial because property operations is a volume business: small time savings repeated across thousands of workflows can free up significant capacity.

The emphasis on predictive intelligence is also notable. Predictive maintenance, lifecycle tracking, and proactive issue identification can materially change both cost and tenant experience, but they require reliable data capture and consistent workflow completion. Visitt’s claim that it combines large operational data sets with continuous onsite feedback loops is important here, because prediction only becomes useful when it is actionable inside the team’s daily tools. If the platform can surface early warnings in the same place where work is assigned and executed, the distance between insight and action gets much smaller.

This is also where onboarding becomes strategic. Many CRE platforms fail not because the product is weak, but because implementation is slow and adoption is uneven across properties. Visitt’s mention of proprietary onboarding technology and scaled customer experience support suggests it’s trying to solve the last-mile problem: turning a promising platform into a consistent operating standard across all sites. In operational software, that last mile is often where ROI is won or lost.

For the ai world organisation, these product directions map closely to the real conversations we host and curate across our ecosystem: AI agents that reduce manual overhead, automation that closes loops reliably, and predictive intelligence that is integrated into decision-making rather than delivered as separate reports. These are the “how” questions leaders bring to ai conferences by ai world—how to deploy, how to govern, how to measure, and how to ensure adoption across teams with different levels of digital maturity.

As a community, we’re also seeing the agenda shift toward domain-specific AI interfaces—AI that is trained not just on general language patterns but on the work patterns of a particular industry. Visitt’s “built around real building operations” narrative is an example of this broader trend toward specialized operational AI. It’s the same pattern that shows up across many ai world organisation events: tools that win are the ones that respect operational reality and embed intelligence directly into workflows that people already depend on.

And as we head into a packed season of the ai world summit programming and related ai world organisation events, these kinds of case studies become valuable not only for PropTech leaders, but for anyone trying to operationalize AI in environments where uptime, accountability, compliance, and service quality matter every day. Whether your organization manages real estate, facilities, campuses, or other distributed physical assets, the underlying lesson is the same: the fastest path to ROI often comes from simplifying the interface, unifying workflows, and using AI agents to remove repetitive coordination from the human workload.

In other words, Visitt’s Series B is not just about growth capital—it is a marker for where “single interface + embedded AI” is headed in commercial operations. And for readers following the ai world summit 2025 / 2026 theme cycle, this story fits squarely into the bigger movement toward agentic AI systems that don’t merely advise, but actively execute within business guardrails.