--- title: "DeepNode raises $5M as demand shifts toward decentralised AI infrastructure" type: "News" locale: "en" url: "https://longbridge.com/en/news/268749311.md" description: "DeepNode has raised $5 million in funding to develop decentralized AI infrastructure, emphasizing practical model performance over raw compute. The project aims to create a collaborative network for AI developers, validators, and compute providers, independent of large central platforms. The funding rounds included strategic investors from Web3 and AI sectors, highlighting competition in decentralized AI platforms. DeepNode's network will use a Proof-of-Work Relevance mechanism to incentivize contributions based on AI output usefulness, with plans for a mainnet launch by Q1 2026." datetime: "2025-12-05T11:26:04.000Z" locales: - [zh-CN](https://longbridge.com/zh-CN/news/268749311.md) - [en](https://longbridge.com/en/news/268749311.md) - [zh-HK](https://longbridge.com/zh-HK/news/268749311.md) --- # DeepNode raises $5M as demand shifts toward decentralised AI infrastructure DeepNode’s latest funding reveals how investor interest is shifting toward decentralised artificial intelligence infrastructure that rewards practical model performance rather than raw compute. The project has secured $5 million across two rounds and plans to build a network where AI developers, validators, and compute providers collaborate without depending on large central platforms. With activity spread across sectors like healthcare, fraud detection, and crypto trading, DeepNode is positioning its system as part of a broader move toward open, permission-less intelligence. The mainnet, due by the end of the first quarter of 2026, places the network’s growth timeline firmly into view. ## Funding momentum builds DeepNode confirmed that it raised $5 million across a $2 million seed round valued at $25 million and a $3 million strategic round valued at $75 million. The fundraising included participation from community members, validators, and infrastructure partners such as WildSageLabs from RoundTable21, Rizzo from DNA, and Gateway.FM. The strategic round brought together Web3 and AI infrastructure investors, including Blockchain Founders Fund, Side Door Ventures, TBV, IOBC Capital, Fomo Ventures, and Nestoris. The mix of investors reflects ongoing competition across early decentralised AI platforms, where capital is flowing toward networks that can demonstrate technical foundations rather than consumer-facing applications. ## Network architecture takes shape A core element of DeepNode’s design is its Proof-of-Work Relevance, or PoWR, mechanism. The system evaluates contributions based on how useful the AI output is, allowing models to compete and evolve on live performance rather than relying solely on energy-intensive computation. Contributors earn emissions tied to the relevance and impact of their work, creating an incentive structure shaped by results. This framework is intended to support predictive and decision-making workloads across several industries. The project highlights healthcare diagnostics, fraud detection, and cryptocurrency trading as areas where real-time model competition could offer more adaptive intelligence. The approach reinforces the network’s positioning as infrastructure for open intelligence, where functionality increases as more builders join. ## Base integration advances DeepNode is developing its network on Base, an Ethereum Layer 2 environment that reports transaction costs below $0.01. The project expects the integration to help it combine Ethereum-level security with low fees. Base posted a value move of -4.41% at the time referenced, though this did not change the network’s role in DeepNode’s roadmap. The upcoming mainnet launch by the end of the first quarter of 2026 coincides with ongoing work on foundation-supported domains. These will expand the ecosystem across multiple verticals, creating dedicated spaces for contributors to deploy and scale sector-specific capabilities. ## IP and participation rules evolve DeepNode aims to establish a system where developers retain intellectual property rights while benefiting from shared network effects. Contributors can earn based on performance metrics, and enterprises can participate privately while still drawing from the broader ecosystem’s intelligence. This structure seeks to balance open collaboration with commercial protection in a way that appeals to both early builders and institutional users. The project’s latest update also signals increased activity across decentralised AI teams working on models, compute networks, and validation layers. With more entrants competing to define standards for how decentralised intelligence should operate, DeepNode is positioning its network as a technical foundation rather than a consumer-first platform. 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