ORA plans to use the funds to expand its ecosystem, focusing on research and development of oracles and blockchain infrastructure.
Oracle protocol ORA has closed a $20 million funding round from Polychian, HF0, and Hashkey Capital, among other investors. The protocol is building a technology for tokenizing artificial intelligence models onchain.
The funds will be used to develop ORA’s ecosystem, with a focus on research and development of oracles and blockchain infrastructure, according to an announcement on June 26.
The protocol is working on its optimistic machine learning technology, or opML, that allows blockchain to conduct AI model inference while adding layers of verifiability and traceability. In other words, every AI interaction, such as the AI model used, the data inputs and the outcomes, is recorded and can be verified.
ORA is also introducing a new mechanism called initial model offering (IMO) that enables tokenization of AI models. Based on an ERC-20 token, the mechanism entitles anyone who buys a token to own and share revenue generated by an AI model.
fee is incurred each time an AI model is used onchain, and this fee is distributed to IMO tokenholders through the use of the ERC-7641 Intrinsic RevShare Token, an ERC-20 extension created by the protocol.
ORA launched its onchain AI oracle on Optmism’s OP mainnet in April. According to its team, its operational oracle is the only one capable of effectively handling any size AI model.
“Through optimistic systems and zero-knowledge technology, it will provide secure and efficient onchain machine learning with privacy-preserving features,” said the company in a statement.
Developers are currently exploring several applications using ORA’s technology, as per a spokesperson. Some use cases include processing insurance claims directly onchain based on specific rules and identifying anomalies that deviate from normal patterns. Additionally, AI oracles are being developed to assist in dispute resolutions and settlements by examining data to make neutral decisions.
