Trad.Fi, which lends money to companies buying heavy equipment, said it is partnering with W3, a developer of AI agents for businesses, to deploy $650 million in private credit on the chain over the next 48 months.
The program targets the heavily paper-based US equipment distribution sector, focusing on manufacturing systems, industrial electrical infrastructure and residential solar. By using artificial intelligence to evaluate risk, perform due diligence and price loans, Trad.Fi aims to compress the typical months-long funding timelines for small and medium-sized businesses into a single day.
“Small businesses are losing deals waiting for funding, and the only way to solve that is to move the capital, records and workflow onto programmable rails,” Trad.Fi CEO Alexander Szul said in a statement. “This is what private credit looks like when it finally meets the speed of the real economy.”
Institutional capital is undergoing a structural shift as it interacts with digital asset infrastructure. The tokenization of real-world assets (RWAs), spanning commodities, equities and private credit, is now a $25 billion market, having quadrupled from around $6.4 billion a year ago. It could become a $30 trillion industry by 2030, according to Security Token Market.
The $650 million figure represents Trad.Fi’s targeted equipment funding pipeline over the next four years, the firm said.
In an initial phase, institutional capital from established, traditional private credit lenders will finance the bulk of the underlying equipment loans directly offchain. At the same time, the companies will work on the initial bridge technology, the ability to predict the stability of companies and effect blockchain capital placement.
The long-term goal of the project is a fully programmable treasury where 100% of senior and equity capital flows natively through the Avalanche blockchain.
A tokenized liquidity pool managed by an unidentified third-party operator will launch in the coming weeks. The pool gives eligible investors direct onchain access to equity shares of the private credit generated by the program.
