Trade.fi, which lends money to companies buying heavy equipment, said it is working with W3, a developer of AI agents for enterprises, to deploy $650 million in private credit onchain over the next 48 months.
The program targets the heavy paper-based US equipment distribution sector, focusing on manufacturing systems, industrial electrical infrastructure and residential solar installations. By using AI to evaluate risk, conduct due diligence and price loans, Trade.fi aims to compress financing timelines that typically take months to a day for small and medium-sized businesses.
“Small businesses lose deals waiting for financing, and the only way to fix that is to move capital, records and workflow onto programmable tracks,” Trade.fi CEO Alexander Szul said in a statement. “This is what it looks like when private credit finally catches up with the real economy.”
Institutional capital is undergoing a structural shift as it interacts with the digital asset infrastructure. The tokenization of real-world assets (RWAs) spanning commodities, equities and private debt is now a $25 billion market, quadrupling from nearly $6.4 billion a year ago. According to Security Token Market, this could become a $30 trillion industry by 2030.
The $650 million figure represents Trade.fi’s targeted equipment-financing origination pipeline over the next four years, the firm said.
In the initial phase, institutional capital from established, traditional private credit lenders will finance the bulk of the underlying equipment loans directly offchain. Additionally, the companies will work on early bridge technology, the ability to predict corporate stability, and influence blockchain capital placement.
The long-term goal of the project is to have a fully-programmable treasury with 100% senior and equity capital flowing natively through the Avalanche blockchain.
A tokenized liquidity pool managed by an unnamed third-party operator will launch in the coming weeks. The pool provides eligible investors with direct onchain access to the equity portion of private credit generated by the program.