XYO Partners with Resiliocs to Add Verifiable Data Layer for Climate Risk Modelling

One of the first DePIN projects, XYO, which currently has over 10 million nodes, has partnered with climate analytics platform Resiliocs to introduce a cryptographic verification layer into climate risk modelling systems. According to the company, roughly 80% of those nodes operate outside the traditional Web3 ecosystem. The collaboration aims to strengthen how environmental observations and geospatial data are recorded and verified in predictive modelling for insurers, financial institutions, and infrastructure operators.

Climate modelling is becoming increasingly central to financial decision-making, yet the data pipelines feeding these models remain fragmented, lack strong oversight, and are often difficult to audit.

The XYO and Resiliocs collaboration addresses part of this problem by attaching cryptographic verification to environmental data as it is captured, creating a traceable record of where and when an observation occurred.

Climate risk modelling under scrutiny

Climate risk intelligence platforms have become an important tool for organisations attempting to quantify exposure to physical climate hazards such as floods, wildfires, storms, and extreme heat.

Resiliocs operates in this space, combining climate science, geospatial analytics, and predictive modelling to translate hazard exposure into financial impact. Its platform enables insurers, asset owners, and financial institutions to model how climate events could affect infrastructure, portfolios, and long-term asset values.

However, the reliability of any modelling system depends heavily on the quality and traceability of the underlying data.

Climate-related lawsuits have more than tripled globally since 2017, and in 2018, the Paradise wildfire, the most destructive in California’s history, destroyed nearly 14,000 homes and ultimately left PG&E facing roughly $30 billion in settlement costs.    

Investigations later revealed that corrosion risks and ageing infrastructure concerns had been documented before the disaster. The case raised questions about how risk signals were recorded, shared, and escalated within organisations. In high-stakes incidents like these, accountability often turns on records, specifically what was known, when it was recorded, and whether warnings were acted upon.

As climate risks intensify, regulators and investors are increasingly demanding stronger evidence that the data used in risk modelling is reliable and auditable.

Adding a cryptographic verification layer

The partnership introduces a blockchain-based verification layer designed to strengthen the provenance of environmental observations used in climate analytics.

YO addresses this challenge by separating data from proof. Rather than storing full datasets on-chain, the network records cryptographic verification metadata describing when and where a real-world observation occurred. This model is built on Proof of Origin and generated through bound witness interactions between independent parties. Verification metadata can be anchored to XYO Layer One, a blockchain optimised for scalable, long-lived proof records.

Through the partnership, XYO’s verification layer will be integrated into climate data pipelines to strengthen data capture, provenance, and long-term accountability. Environmental and geospatial observations can be anchored at the moment they are collected, with XYO’s global network of more than ten million nodes providing cryptographic evidence that the observation occurred, creating a verifiable foundation for downstream modelling.

Markus Levin, co-founder of XYO, said the partnership reflects changing expectations around climate analytics.

The idea is that by anchoring cryptographic proof at the moment data is collected, organisations could demonstrate that environmental observations have not been tampered with after the fact.

What XYO actually provides

XYO is one of the earliest decentralized physical infrastructure network (DePIN) project founded in 2018 and designed to collect and verify real-world data through a distributed network of nodes.

The project claims to operate more than 10 million nodes globally, many of which are linked to the COIN mobile application, a gamified platform that rewards users for participating in data validation activities.

At a technical level, the network uses mechanisms such as Proof of Location and Proof of Origin to confirm that real-world events occur at specific locations.

The resulting verification metadata can then be anchored to XYO’s Layer One blockchain, which is designed to store proof records rather than full datasets. This architecture attempts to avoid the scalability issues associated with placing large amounts of raw data on-chain.

In theory, such a system could be applied to industries where location and event verification are important, including logistics, asset tracking, geospatial data collection, and environmental monitoring.

The growing intersection of AI, climate data, and blockchain

The collaboration sits within a broader trend of blockchain projects attempting to position themselves within climate technology and environmental data markets, from carbon credit tracking to supply chain emissions reporting and environmental monitoring

Blockchain-based verification can help address questions around data integrity, but XYO’s model attempts to go a step further by strengthening the validity and timeliness of the underlying observations themselves. Because the network relies partly on a distributed user base interacting through the COIN app, it creates a mechanism for capturing real-world events that might otherwise go unrecorded by traditional monitoring systems.

Smaller environmental incidents often fall below the threshold of national reporting. A minor wildfire in a rural area, a localized flood, or an infrastructure issue may be observed by residents long before it appears in official datasets or media coverage. In systems like XYO’s, individuals using the COIN app could document such events by capturing geotagged observations, with metadata about the time and location cryptographically verified through the network.

Consider a scenario where a small brush fire breaks out near a piece of infrastructure such as a transmission line or pipeline corridor. The fire may be quickly contained and never reported by major news outlets, yet it could still be relevant for climate risk assessments or infrastructure monitoring. A local COIN app user could record the event on-site, providing timestamped and location-verified evidence of the fire’s occurrence. That observation could then be incorporated into datasets used by platforms like Resiliocs, providing an additional data point that might otherwise have been missed.

In this way, decentralized participation can function as a supplementary observation layer, capturing localized environmental signals that centralized monitoring systems may overlook.

From a Dream to a Reality 

For Resiliocs, the partnership offers a way to differentiate its climate risk platform by emphasizing traceable and defensible data pipelines.

XYO on the other hand attempts to apply decentralized infrastructure to real-world data verification beyond traditional crypto use cases.

Climate analytics platforms already operate in a highly technical ecosystem dominated by scientific modelling frameworks and specialized environmental data providers.

However, as climate risk becomes increasingly financialized and legally contested, the ability to demonstrate data provenance may become more important. In that context, verification layers like the one provided by XYO could find a niche role, even if they remain a relatively small component of the broader climate intelligence stack.

Disclaimer: This article is provided for informational purposes only. It is not offered or intended to be used as legal, tax, investment, financial, or other advice.