Antal was built from a specific frustration. When co-founder and CEO Roberto Pernicone was scaling a private credit lender, he kept running into the same wall. The capital was there. The borrowers were there. What was not there was a way to move files fast enough to keep up with either.
Every loan required a chain of people: someone to interpret the inquiry, someone to chase documents, someone to coordinate title, insurance, entity checks, and appraisals, someone to prepare the underwriting package, and someone to route it to the right decision-maker. Each handoff was a delay. Each delay was a borrower who might not be there by the time the term sheet went out.
Pernicone eventually left that lender with a specific conviction: the operational layer underneath private credit was broken, and no existing tool was going to fix it. So he built one.
What Antal Capital Does
Antal is an AI operating layer for private credit lenders. The company lets lenders encode their credit box once and then hands the file to a stack of AI agents that run the work from first borrower message to a complete, underwriting-ready package.
The agents size the deal, issue a conditional term sheet, collect and verify documents, coordinate third-party checks, flag exceptions, and assemble the file. A conditional term sheet can go out within three minutes of a borrower’s first message. A complete underwriting package lands at the lender’s desk days later, with every number sourced and every document verified. The lender makes one decision: clear to close.
Nothing irreversible happens without a human sign-off. Declines, exceptions, funding approvals, and overrides all stay at the lender’s desk. The agents handle the coordination work around the credit decision. The credit decision itself stays human.
The Problem Antal Capital Is Solving
Private credit has grown into a more than $3 trillion asset class globally, and it is still growing. But the operational infrastructure underneath most non-bank lenders has not kept pace. Many lenders running fix-and-flip, DSCR, bridge, and ground-up construction loans are still working through email threads, spreadsheets, and vendor portals that do not talk to each other.
The standard response to growth has been hiring. More volume means more processors, more coordinators, more analysts. That works up to a point. It becomes expensive and fragile when a lender is trying to scale originations without a proportional increase in headcount.
“Lenders do not need another system that tells their team what task is next,” Pernicone said. “They need agents that can execute the work between human decisions while preserving the lender’s guidelines, brand, controls, and audit trail.”
One Record, Start to Finish
Every action on an Antal loan is written to an append-only record as it happens. Borrower communication, guideline application, document collection, vendor checks, exceptions, approvals, and funding events all land in one place. At payoff, the lender can export a complete binder for note buyers, warehouse lines, LPs, or auditors without rebuilding the story from scattered inboxes.
The platform is fully white-labeled. Borrowers interact with the lender’s AI loan officer under the lender’s brand at every stage. Antal is not visible to the borrower.
Why It Matters Now
Private credit is not slowing down. More capital is flowing in, more borrowers are looking for non-bank options, and lenders that can move faster without sacrificing documentation or accountability will be better positioned to capture that demand.
Antal’s argument is simple: the constraint for most private lenders right now is not capital or borrowers. It is the number of touches required to get a file from inquiry to funded. If that number comes down, the desk scales. If it does not, headcount will always be the ceiling.
For private credit lenders looking to grow, that is the problem worth solving first. More information is available at antalcapital.com.
