Stop guessing which lenders fit your real estate deal.
LYNDIFY helps real estate investors, brokers, and referral partners identify lenders that match their deal criteria before sending a quote request.
Match by property type, loan amount, leverage, geography, use of funds, borrower profile, term, and deal structure.
Know which lenders fit before you submit.
Many real estate investors and brokers waste time sending deals to lenders that are not a fit. The lender may not lend in the state, may not accept the property type, may not like the leverage, or may not offer the requested loan structure.
A lender may look active, but still decline the deal because the state, property type, loan size, term, or structure does not match their guidelines.
When deals are sent broadly, lenders are more likely to ignore requests that do not clearly fit their current lending criteria.
Manual lender searches create more back and forth, more dead ends, and less clarity around which lenders should receive the deal first.
LYNDIFY is lender matching software built for non-owner-occupied real estate deals. Instead of searching a directory or blasting every lender, users review matched lenders first and manually choose who receives the quote request.
Add the property type, location, loan amount, use of funds, borrower profile, leverage, term, and deal details.
LYNDIFY ranks lenders based on how closely each lender fits the deal scenario and removes lenders that do not meet key criteria.
You manually choose which matched lenders receive quote requests. LYNDIFY does not automatically send requests for you.
LYNDIFY supports common real estate financing scenarios where lender fit changes based on loan type, property details, leverage, and borrower profile.
Match rental property and cash-flow based loan scenarios with lenders that support DSCR programs.
Match purchase and rehab scenarios based on ARV, scope, budget, experience, and leverage profile.
Identify lenders that fit short-term bridge financing, refinance, cash-out, and transition scenarios.
Match ground-up construction projects based on project costs, LTC, property type, and borrower experience.
Support multifamily, mixed-use, and commercial real estate scenarios where lender appetite can vary widely.
Help users identify private lenders and investment property lenders that align with the deal before outreach.
LYNDIFY is built for people placing non-owner-occupied real estate loans who need a faster way to compare lender fit before sending the deal.
Use LYNDIFY to find lenders for investment property deals without manually researching every lender first.
Help borrowers and investors place deals faster by comparing matched lenders before requesting terms.
Support clients with a more organized way to match deals with lenders that fit the scenario.
LYNDIFY supports lender matching across multiple real estate financing strategies.
Quick answers about real estate lender matching, loan placement, and how LYNDIFY helps users find lenders that fit.
Lender matching is the process of identifying lenders that fit a deal based on specific loan criteria, property details, borrower profile, and lender guidelines.
Directories require you to search manually. LYNDIFY matches your deal based on inputs and criteria, then helps you focus on lenders that fit.
No. Users review matched lenders and manually choose which lenders receive quote requests.
Yes. Users can request quotes from multiple matched lenders and compare lender responses inside the platform.
No. LYNDIFY identifies lenders that fit the deal profile, but all lending decisions remain subject to lender underwriting and approval.
LYNDIFY supports DSCR, fix and flip, bridge, new construction, commercial, hard money, and private lending scenarios.
Submit your real estate deal, review matched lenders, and request quotes only from lenders that fit your scenario.
LYNDIFY is a lender matching and capital alignment platform for real estate investment transactions.

LYNDIFY is a lender matching and capital alignment platform for real estate investment transactions.

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