The Decentralized Map Paying for Data That Google Uses for Free

OpenLedger, a blockchain infrastructure firm building out AI systems for transparent data attribution, is expanding its ecosystem with the addition of SenseMap, a new decentralized mapping network.

The platform enables users to contribute real-time information such as safety, crowd levels, and noise, all of which are verified on-chain and used to build an open, community-owned map.

“In places traditional maps overlook, local contributors can fill the gaps by sharing real-time context—roads, crowd density, safety, or accessibility details,” Ram Kumar, core contributor at OpenLedger, told Decrypt.



Each submission is tied to a verified on-chain identity and reviewed by community validators who earn reputation over time. Reliable contributors gain more influence in the system, while inaccurate or spam entries are flagged and penalized to maintain the trustworthiness of the data.

Asked whether the open model risks low-quality data, Kumar said accuracy is maintained through on-chain reputation, staking, and validator review. “Spamming isn’t just discouraged, it’s economically unsustainable,” he said.

Alphabet, the parent company of Google, reported $82.5 billion in Google Services revenue for Q2 2025, up from $73.9 billion a year earlier, according to its latest earnings release. The services revenue segment includes Maps, Search, and Google Play.

While the company does not break out Maps revenue, analysts have noted its commercial potential as far back as 2019, when Morgan Stanley’s Brian Nowak projected that Google Maps could generate roughly $4.8 billion annually. Later reports indicated that the platform’s ad revenue was on track to reach $11 billion by 2023.

Decrypt reached out to Google to confirm this figure and ask what they think of decentralized alternatives to their product.

OpenLedger claims that as SenseMap expands, its accuracy improves rather than declines, driven by a reputation-based validation system that rewards consistent contributors and verifies every data point through its on-chain Proof of Attribution protocol.

The protocol works by linking each data contribution to a verifiable on-chain record showing who created it, when, and how it’s used in downstream AI models, ensuring that “every new data point strengthens the network’s accuracy instead of diluting it,” Kumar said.

“As the network scales, trust is maintained through a reputation-based validation system,” Kumar explained. “The more consistent and reliable a contributor’s data, the higher their validator weight.”

Other observers note that maintaining accuracy in decentralized mapping depends less on central coordination and more on verifiable data between independent nodes.

“Trust comes from reproducibility,” Arie Trouw, co-founder and CEO of decentralized physical infrastructure network XYO, told Decrypt. When multiple nodes reach the same result through cryptographic proofs, accuracy is established by consensus rather than control, Trouw explained.

He added that decentralized mapping works best where centralized data collection falls short, such as in “developing regions, disaster zones, or rapidly changing urban areas,” where real-time, verifiable updates are most needed.