Multicoin Capital said on Sept. 30 that it has invested in Grass through its hedge fund and venture fund, adding exposure to a DePIN project focused on internet data collection and retrieval infrastructure. Grass says it uses token incentives to aggregate unused residential bandwidth from more than 6 million contributors worldwide, creating a base layer for crawling and parsing public internet data. The network currently serves leading AI labs with model pretraining data and, according to the company, is already profitable. Official figures cited by Grass show $17 million in revenue for 2025 and another $17 million in the first half of 2026. The company expects full-year 2026 revenue from its training data business alone to reach $75 million. Grass also said it is expanding beyond training data into real-time contextual retrieval for inference workloads. As part of that push, it plans to launch a Contents API and a Search API aimed at meeting live data retrieval and web indexing needs for AI agent systems during runtime.
Multicoin Capital said on Sept. 30 that it has invested in Grass through its hedge fund and venture fund.
Grass uses idle residential bandwidth to build public internet data infrastructure
Grass, a decentralized physical infrastructure network, says it uses token incentives to aggregate unused home internet bandwidth from more than 6 million contributors worldwide. That network is used to build underlying infrastructure for crawling and parsing public internet data.
The project currently provides model pretraining data support to leading artificial intelligence labs and has already become profitable, according to the official description.
Revenue figures released by the project
Official data cited by Grass show that the project generated $17 million in revenue in 2025. Revenue for the first half of 2026 also reached $17 million. Grass said it expects revenue from its training data business alone to total $75 million for full-year 2026.
Expansion into real-time contextual retrieval
Beyond training data, Grass said it is moving into real-time contextual retrieval for the inference stage. The project plans to roll out a Contents API and a Search API to serve AI agent systems that need live data retrieval and web indexing during runtime.
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