2MS LANDSCAPING LLC

Flipper active in Gainesville, GA. 15 acquisitions, $3.63M tracked volume, $242,033 average price, latest observed Mar 2025.

Gainesville, GAflipperorganization
53% cash2 observed lenders$242,033 avgLatest Mar 2025

Investor profile snapshot

2MS LANDSCAPING LLC is a flipper real estate investor active in Gainesville, GA with 15 recorded acquisitions totaling approximately $3,630,500. Recorded purchases appear concentrated in a tighter local market footprint. The most recent recorded purchase was in March 2025, so the visible activity window still looks fairly recent from a deed-record standpoint.

Recorded purchases skew toward Single Family Residential and Vacant Land. Average observed purchase price sits near $242,033, which reads as mid-market acquisition pricing. Behavioral signals point to flip-oriented behavior, cash-heavy execution, and frequent private-lender financing within the recorded deed activity.

Observed window
February 2022 to March 2025

About 3 years of observed acquisition activity

Latest recorded purchase
March 2025

Still fairly recent, even if buying pace may be uneven

Market footprint
1 state / 1 metro

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

15
Transactions
15
Properties
$3.63M
Total Volume
$242,033
Average Price

Property Types

Single Family ResidentialObserved
Vacant LandObserved
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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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Easy StreetSkyBeam Capital

Who else does Easy Street fund?

This investor uses 2 observed lenders. See borrower activity, lender market share, and verified contacts in Gainesville, GA.

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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 2MS LANDSCAPING LLC focus on?

Public records associated with 2MS LANDSCAPING LLC show activity in Single Family Residential, Vacant Land across Gainesville, GA.

How many properties are associated with 2MS LANDSCAPING LLC?

Public records show approximately 15 properties and 15 recorded transactions associated with 2MS LANDSCAPING LLC in this dataset.

Which lenders has 2MS LANDSCAPING LLC worked with?

Recent recorded mortgage activity references Easy Street, SkyBeam Capital. Full lender history is available in SFR Analytics.

How recent is 2MS LANDSCAPING LLC's activity?

Records show activity from 2022 through 2025, with the most recent observed purchase recorded in March 2025.

Where is 2MS LANDSCAPING LLC active?

Recorded activity is concentrated in Gainesville, GA, with footprint across 1 state and 1 metro 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.