Nevermined

YOUR DATA & AI UNCHAINED

Nevermined champions open Data and AI to lower the barrier of entry for AI adoption and advancement and opposes the centralization of AI development and training data.

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Precision AI needs precise data. We make walled data easy to share, easy to compute & easy to reward.

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Data Availability Tools

NVM allows organizations to register, tokenize and transform data so that it can be used in analytics by algorithms and AIs. Learn More
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Open AI & Compute Services

NVM facilitates the use of our native AI services, as well as “Bring your own model” to be trained on NVM’s ecosystem of data Learn More
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Artifact Management & Incentives

NVM has designed a scalable way to monetize walled / siloed data by tracking data provenance while attributing sources and collecting royalties Learn More

Nevermined builds open Data & AI tools powered by Web3 tech

Decentralized Access Control

  • Tokengating Data
  • Subscription NFT
  • Access Credits
  • File Access NFT
  • Decentralized Storage Encryption

Data In-Situ Computation

  • Federated Computation
  • ML & AI Model Royalties
  • AI & Machine Learning Industrialization

Data & AI Incentives

  • Royalties
  • Rewards
  • Dynamic pricing
  • Marketplace Framework
  • Collateralization
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The next wave of AI adoption will be defined by:

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Data Availability

Organizations that have access to data and models beyond the enterprise and have well-defined processes for data governance and management will be best positioned to leverage the advancements and adoption in AI.

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AI Precision & Trust

Specialized AI models are incredibly valuable as they allow organizations to solve specific problems and optimize processes within their industry. The result is significant cost savings and improved efficiency based on accurate outputs that organizations can trust.

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AI Model Industrialization

Rapid advancements in hardware, software and algorithms will make it possible to build and deploy AI systems at scale, while making it even easier for organizations to implement without the need for in-house data and AI engineers.

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