Dwelly closes major funding round to transform rentals with AI
London-based proptech startup Dwelly has secured more than €79.3 million to accelerate the growth of its AI-driven rental marketplace, positioning itself as a key player in Europe’s evolving housing and technology landscape. The fresh capital will be used to enhance the platform’s technology, deepen its presence in major cities and expand its product offering for both landlords and tenants.
AI at the core of Dwelly’s rental marketplace
Dwelly uses advanced machine learning models and AI algorithms to streamline the rental journey from search to signed lease. The platform analyzes real-time market data, historical pricing, neighbourhood trends and user behaviour to deliver more accurate property matches and dynamic pricing recommendations.
For tenants, the service promises faster discovery of suitable homes by ranking listings according to budget, commuting patterns and lifestyle preferences. For landlords and property managers, Dwelly offers automated tenant screening, rental yield insights and tools to reduce vacancy periods.
Scaling across key European cities
The new funding will support Dwelly in expanding beyond London into other high-demand rental markets across Europe. The company plans to invest in local market data integrations, partnerships with large property portfolios and improved customer support for cross-border renters, such as students and remote workers.
Industry observers see the raise as further evidence that AI-powered property technology is moving from niche to mainstream. With housing affordability and supply constraints high on the public agenda, investors are increasingly backing platforms that promise greater efficiency, transparency and better use of existing housing stock.
Rising competition in AI-led housing solutions
Dwelly enters a competitive field of digital rental platforms, but its emphasis on end-to-end automation, from property discovery to contract management, is designed to differentiate it from traditional listing sites. By leveraging data analytics and predictive models, the startup aims to reduce friction for all parties and set a new standard for how urban rentals are discovered, priced and managed.