Ocean Alternatives

If you're looking for a different Ocean alternative, Oasis is a strong contender. It's designed to provide scalable, secure foundations for Web3 and AI work, with a particular emphasis on smart privacy. The modular design, including the Oasis Sapphire that's the first production-ready confidential Ethereum Virtual Machine (EVM), makes it a good foundation for decentralized AI, DeFi and other privacy-concerned use cases. Developers can retrofit privacy to existing dApps on any EVM network with the Privacy Layer, so it's a good tool for protecting data.

Another contender is Dappier. The company's platform is designed to empower content creators by letting them sell access to their data and content to AI companies while keeping control over how it's used and how much it's worth. With features like self-service tuning of content for AI training models, deployment of AI-powered chatbots and real-time content recommendations, Dappier is suited for news, finance and sports. The multi-tenant architecture and isolated data clusters ensure data is kept private.

If you're a business that wants to build AI applications on your own data, Credal is a suite of tools to do so. Credal has built-in security, access controls and compliance features, as well as point-and-click integration with a variety of data sources. Its Retrieval Augmented Generation (RAG) technology lets you build secure and enterprise-ready AI applications. Credal's security and compliance focus makes it a good option for companies that have to deal with sensitive data like GDPR and HIPAA.

Last, Dataloop is an AI development platform that includes data curation, model management and pipeline orchestration to speed up AI application development. With automated preprocessing and strong security controls that meet major standards, Dataloop is designed to facilitate collaboration and speed up development while maintaining high security. It's a good option for companies that have lots of unstructured data to manage and that want to deploy AI models efficiently.