Wint raises $36 million Series D to scale AI-powered water intelligence globally

Wint has raised $36 million in Series D funding to expand its AI-powered water intelligence platform, as building owners, contractors, insurers, and facility operators increasingly look to technology to manage water as both an operational resource and a source of financial risk.

The round was co-led by LIP Ventures and Inven Capital, with Wint planning to use the capital to accelerate product development and expand its presence in global markets. The company did not disclose a valuation as part of the announcement.

The financing represents the latest stage in Wint’s expansion following a $35 million Series C in 2023, which was co-led by Inven Capital and Insight Partners, and a $15 million Series B led by Insight Partners in 2022.

Turning water systems into real-time data

While water management has traditionally relied on meters, utility bills, maintenance inspections, and basic leak sensors, Wint is attempting to make building water systems continuously observable.

The company combines connected meters, valves, control units, and AI software to analyze how water moves through buildings in real time. Rather than simply detecting whether water is present where it should not be, the system learns the normal behavior of individual water systems and looks for deviations.

Wint says its AI models have been developed using tens of millions of hours of real-world water-flow data covering systems ranging from building mains and domestic hot water to heating, ventilation, and air conditioning (HVAC) loops and cooling towers. The models use this data to distinguish normal consumption from patterns that may indicate problems such as a pinhole leak, stuck toilet, burst pipe, or equipment malfunction.

When the system determines that an event requires intervention, it can alert building operators and automatically close connected valves. Importantly for environments such as data centers, hospitals, and other critical infrastructure, Wint’s control units can make detection and shutoff decisions locally rather than depending entirely on a connection to the cloud.

That distinction moves the technology closer to autonomous infrastructure management: AI is not simply analyzing a building and sending information to a human, but can be authorized to take physical action when predefined risk conditions are met.

Expanding from leak detection into building intelligence

Wint has also been broadening the platform beyond emergency leak prevention.

Its Water Insights technology analyzes granular consumption data over longer periods, looking for inefficiencies and behavioral patterns that might be difficult for facility teams to identify manually. The system can benchmark performance, highlight persistent overconsumption, and identify equipment or configuration problems before they become larger operational issues.

The company added another layer in late 2025 with AI-based water temperature analysis. Its initial application, a Boiler Health Analyzer, correlates water temperature with flow data to detect patterns associated with overheating, underheating, or insufficient boiler capacity.

The progression is significant because it expands Wint’s potential role from protecting buildings against catastrophic leaks toward continuously analyzing how mechanical systems are performing.

Over time, that creates opportunities for water intelligence to become another component of the broader smart-building technology stack, alongside energy management, HVAC monitoring, building management systems, and predictive maintenance platforms.

Insurance is becoming an important part of the equation

The financial case for water intelligence also extends beyond utility savings.

Water leaks can result in expensive property damage, business interruptions, construction delays, and insurance claims. This has created an unusual intersection between AI infrastructure technology and insurance, where preventing an incident can have significantly more economic value than simply reducing water consumption.

HSB, part of Munich Re, has partnered with Wint around its water leak technology and performance warranty. Munich Re says a study comparing construction sites protected by Wint against unprotected sites found 73% fewer claims and 90% lower payouts at Wint-protected locations.

That relationship illustrates a potentially important direction for industrial AI. If insurers can use data from monitoring systems to quantify reductions in physical risk, technologies such as Wint could increasingly influence not only facility operations but also underwriting requirements, deductibles, premiums, and risk-management standards.

Wint enters its next stage of expansion

Wint entered 2026 with substantially greater scale than when it completed its previous institutional funding round.

The company reported that it had sold more than 30,000 systems and expanded its customer base by more than 40% to nearly 600 enterprises by the end of 2025. Wint also said its technology helped more than 1,500 facilities save 1.15 billion gallons of water during the year while preventing more than 1,300 water-damage incidents representing an estimated $100 million in potential losses. Those figures are company-reported rather than independently audited performance statistics.

Wint also received a strategic investment from global property group Grosvenor in December 2025, with Grosvenor planning to expand use of the technology across its real estate portfolio.

The new $36 million Series D gives Wint additional capital to push that model into more buildings and markets.

The larger question is whether water management follows a similar trajectory to energy management, where increasingly granular sensors, centralized data, and automated controls turn what was once largely passive infrastructure into something actively optimized by software.

For Wint, that would make leak prevention only the starting point. The longer-term opportunity is to make the water systems running through commercial buildings, construction projects, data centers, and other critical facilities measurable, predictable, and increasingly autonomous.