Stockholm's Vessla Debuts With $3.3M Pre-Seed Round to Put AI Agents to Work Across Property Portfolios

In practice, this means customers are not asked to replace their property management, leasing or accounting tools. The agents work through those tools, which keeps the rollout closer to an add‑on than a system migration for large operators.

The company's longer‑term goal is an operating system for entire property portfolios that links leasing, building operations and investment planning. Property teams set the priorities and take the necessary actions, while the agents look for ways to raise income and cut costs.

Founder Kasper Janehag began his career in the space industry and worked on NASA's Mars 2020 mission. He later led major AI projects at QuantumBlack, the AI arm of McKinsey. Chief scientist Arash Dabiri has built and tested agentic AI applications at Andon Labs and QuantumBlack. Chief executive Orman Gazvini advised large software companies at McKinsey and worked on strategy and mergers and acquisitions at Pophouse. Other members of the founding team previously worked at Legora, Stanford and Netlight.

"We believe AI will fundamentally change how property companies operate, from maintenance and costs to leasing and rental income. The hard part is making it work at scale across the systems and processes those companies already rely on," Gazvini said. He added that as AI takes on more of the execution, people's judgment, relationships and responsibility become more important.

Janehag said the real test for any AI product is whether it can handle the messy, consequential work of a complex business. According to him, that requires deep integrations with large amounts of context, rigorous evaluation and clear limits on what agents can do, and Vessla is being built to that standard across whole portfolios.

Felix Martinez, a partner at Seedcamp, said the team's experience building advanced AI applications, and in particular deploying them in high‑stakes enterprise settings, explains the strong interest that leading property companies have shown so quickly.

Oliver Molander, founder and partner at the Inception Fund, said AI is moving faster than most companies can keep up with and that software built in‑house today can be outdated within three months. In his view, winners in vertical AI become their customers' external AI research and development department, continuously turning new technology into practical value.

Vessla enters a field that has attracted growing investment. New York‑based Uniti raised a $12 million Series A led by Pathlight in July to build agents that handle leasing, maintenance and collections for self‑storage and multifamily operators. ProptechOS offers an agentic suite for real estate companies, and EliseAI has raised a $250 million Series E.

Venn, an Israeli‑founded real estate technology company, recently acquired US‑based Zuma for $50 million. Zuma builds AI agents for multifamily housing that capture leads, schedule tours, collect rent and respond to residents, and Venn serves more than 270 owners and operators.

Figures from the Center for Real Estate Technology and Innovation show that AI‑native proptech companies raised around $4.5 billion in venture financing in 2025, and that their share of all proptech venture funding rose by 42 percent.

Agent‑based software is also spreading into other sectors. FLÆ Robotics has installed an AI receptionist in more than 60 hotels, and Causa Prima has raised a $20 million seed round for AI agents that settle business‑to‑business invoices.

Uniti's chief executive, Francesco Decamilli, has noted that many property management records have already been digitised while much of the customer‑facing work is still done by hand. That split between recorded data and manual coordination is the area where a growing group of agent‑based companies, Vessla among them, is building products.

Vessla describes its pre‑seed round as oversubscribed. The company is based in Stockholm and positions its platform for commercial real estate teams that run several software systems side by side.