NOLA MAGNOLIA LLC

Flipper active in Port St. Lucie, FL. 10 acquisitions, $3.14M tracked volume, $314,473 average price, latest observed Mar 2026.

Port St. Lucie, FLflipperorganization
30% cash2 observed lenders$314,473 avgLatest Mar 2026

Investor profile snapshot

NOLA MAGNOLIA LLC is a flipper real estate investor active in Port St. Lucie, FL with 10 recorded acquisitions totaling approximately $3,144,725. Recorded purchases span 2 metros inside the same state footprint, which suggests a broader local-to-regional buy box. The most recent recorded purchase was in March 2026, so the visible activity window still looks fairly recent from a deed-record standpoint.

Recorded purchases skew toward Single Family Residential and Townhouse. Average observed purchase price sits near $314,473, which reads as mid-market acquisition pricing. Behavioral signals point to flip-oriented behavior, regular cash buying, and frequent private-lender financing within the recorded deed activity.

Observed window
April 2024 to March 2026

Roughly 23 months of recorded buying activity

Latest recorded purchase
March 2026

Recent enough to suggest the profile is still active

Market footprint
1 state / 2 metros

Activity appears concentrated in a narrower local market footprint

Strategy read
Flip-oriented

Derived from observed cash, financing, and flip-like transaction patterns

About this profile

SFR Analytics builds investor profiles from observed deed, mortgage, and assessor records. Use these metrics to compare acquisition patterns, market footprint, and financing signals across investors. Public-record coverage and entity resolution vary by county, so counts represent observed activity in our dataset rather than a complete legal ownership record.

Transaction Summary

10
Transactions
10
Properties
$3.14M
Total Volume
$314,473
Average Price

Property Types

Single Family ResidentialObserved
TownhouseObserved
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Financing Signal

Recorded mortgage data links this profile to 2 observed lenders. The public page shows a sample; Private Lender Radar is where lender teams can review the full lender history, borrower activity, lender share, and contact workflow.

Sample observed lenders

Showing 2 of 2 observed lender relationships.

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HouseMaxRenovo Financial

Who else does HouseMax fund?

This investor uses 2 observed lenders. See borrower activity, lender market share, and verified contacts in Port St. Lucie, FL.

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Lenders

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Wholesalers & flippers

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Data teams

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Frequently asked questions

What type of real estate does NOLA MAGNOLIA LLC focus on?

Public records associated with NOLA MAGNOLIA LLC show activity in Single Family Residential, Townhouse across Port St. Lucie, FL.

How many properties are associated with NOLA MAGNOLIA LLC?

Public records show approximately 10 properties and 10 recorded transactions associated with NOLA MAGNOLIA LLC in this dataset.

Which lenders has NOLA MAGNOLIA LLC worked with?

Recent recorded mortgage activity references HouseMax, Renovo Financial. Full lender history is available in SFR Analytics.

How recent is NOLA MAGNOLIA LLC's activity?

Records show activity from 2024 through 2026, with the most recent observed purchase recorded in March 2026.

Where is NOLA MAGNOLIA LLC active?

Recorded activity is concentrated in Port St. Lucie, FL, with footprint across 1 state and 2 metros in this dataset.

How is associated activity determined?

SFR Analytics matches recorded deeds, mortgages, and assessor records across counties to assemble investor-level activity profiles. Matches use name normalization, address co-occurrence, and entity signals from public records. Profiles are directional - they reflect what is observable in deed-backed data and may not capture every off-record transaction or affiliated entity.

Data sources & methodology

SFR Analytics builds these profiles from recorded deeds, mortgages, assessor records, and entity matching. They are designed for market research: comparing acquisition activity, property focus, market footprint, and financing signals across investors. Coverage varies by county and record type, so counts reflect observed activity in our dataset.