At Unitas Funding, technology has a clear purpose: make the lending process faster and more efficient without losing the personal relationships and human judgment that real estate investors rely on.
Artificial intelligence is creating new opportunities to do that. What started with relatively simple uses, such as helping draft emails or organize information, is becoming a more significant part of how lending businesses operate. AI can help teams prepare for borrower conversations, process documents, identify potential fraud, evaluate construction budgets and manage workflows more efficiently.
In sales, AI does not need to replace the conversation between a borrower and a lending professional. Instead, it can help organize information about a borrower or opportunity so the salesperson enters the conversation with greater context and can have a more relevant, informed discussion from the start.
The same approach can extend throughout the lending process. AI can assist with reading and organizing loan documents, identifying missing information and managing the checklists that accompany underwriting and closing. As those capabilities improve, technology can take on more repetitive work while Unitas's lending professionals remain focused on analysis, decision-making and the borrower relationship.
Construction lending presents another opportunity. Technology can help teams evaluate construction budgets against available cost information and improve the management of draws and other ongoing processes. AI can also support fraud detection by identifying inconsistencies or patterns that warrant closer review.
For Unitas, greater efficiency behind the scenes only matters if borrowers ultimately benefit from it.
The company's existing processes demonstrate what that can look like. Unitas offers pre-approvals within 24 hours and closings in as little as 10 days. Underwriting, inspections, draw approvals and funding are kept in-house, with construction draws managed within 24 to 48 hours.
AI has the potential to build on those capabilities by helping teams process information and surface potential issues earlier. That can give lending professionals more time to focus on helping borrowers move transactions forward. Over time, reducing the resources required to originate and manage loans may also create opportunities to lower costs and pass some of those efficiencies on to borrowers.
Efficiency behind the scenes means little if it comes at the cost of access. As lending becomes more automated across the industry, some borrowers are finding it harder to reach an actual person — no direct line, no one who knows the deal, no one who can walk the property.
Unitas takes the opposite approach wherever it can. Account executives are assigned to a market, not a queue, and spend time in the areas they cover — building relationships with local contractors and suppliers and developing a working knowledge of market conditions that a document or a dashboard can't fully capture. Where Unitas has a dedicated AE on the ground, that means an in-person property visit when it matters. Unitas continues to expand that regional coverage, and the same standard of access applies everywhere: a direct line to someone who knows the deal, in person whenever geography allows it.
That accessibility carries through the relationship regardless of location. Borrowers aren't routed through a general line — they have their AE's direct phone number and can expect a timely response from someone who already knows their deal. AI can help that AE prepare and follow up faster. It doesn't replace the fact that a real person answers.
That kind of access reflects a broader principle: efficiency does not mean removing people from the process.
Real estate investors may need to discuss the nuances of an acquisition, work through an unexpected issue during construction or understand why additional information is required. In those situations, an automated interaction is not necessarily a better interaction.
Private real estate lending also does not lend itself to a single, standardized approach. Every lender has its own underwriting guidelines, risk parameters and processes, while every property, borrower and business plan can present different considerations.
That makes human oversight especially important as AI becomes more capable. A system may be able to identify an inconsistency in a document or flag something unusual in a construction budget, but an experienced lending professional still needs to interpret that information and determine what it means for a specific transaction.
For Unitas, the opportunity is not to automate the relationship, but to improve the work surrounding it. Used effectively, AI can give lending professionals better information, streamline processes and help borrowers move more quickly, while preserving the direct access and human judgment that remain essential to successful real estate lending.