BEECHWOOD PROPERTIES LLC

Flipper active in Connecticut. 29 acquisitions, $4.13M tracked volume, $142,525 average price, latest observed Feb 2025.

Connecticutflipperorganization
52% cash2 observed lenders$142,525 avgLatest Feb 2025

Investor profile snapshot

BEECHWOOD PROPERTIES LLC is a flipper real estate investor active in CT with 29 recorded acquisitions totaling approximately $4,133,231. Recorded purchases appear concentrated in a tighter local market footprint. The most recent recorded purchase was in February 2025, so the visible activity window still looks fairly recent from a deed-record standpoint.

Recorded purchases skew toward Condo, Duplex, and Single Family Residential. Average observed purchase price sits near $142,525, which reads as entry-level to lower-middle price points. Behavioral signals point to flip-oriented behavior, cash-heavy execution, and frequent private-lender financing within the recorded deed activity.

Observed window
March 2022 to February 2025

About 3 years of observed acquisition activity

Latest recorded purchase
February 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

29
Transactions
29
Properties
$4.13M
Total Volume
$142,525
Average Price

Property Types

CondoObserved
DuplexObserved
Single Family ResidentialObserved
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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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KiaviRge Properties LLC

Who else does Kiavi fund?

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

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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 BEECHWOOD PROPERTIES LLC focus on?

Public records associated with BEECHWOOD PROPERTIES LLC show activity in Condo, Duplex, Single Family Residential across Connecticut.

How many properties are associated with BEECHWOOD PROPERTIES LLC?

Public records show approximately 29 properties and 29 recorded transactions associated with BEECHWOOD PROPERTIES LLC in this dataset.

Which lenders has BEECHWOOD PROPERTIES LLC worked with?

Recent recorded mortgage activity references Kiavi, Rge Properties LLC. Full lender history is available in SFR Analytics.

How recent is BEECHWOOD PROPERTIES LLC's activity?

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

Where is BEECHWOOD PROPERTIES LLC active?

Recorded activity is concentrated in Connecticut, 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.