GAZ HOLDINGS LLC

Multi entity active in Kokomo, IN. 20 acquisitions, $7.87M tracked volume, $393,663 average price, latest observed Nov 2025.

Kokomo, INmulti-entityorganization
0% cash2 observed lenders$393,663 avgLatest Nov 2025

Investor profile snapshot

GAZ HOLDINGS LLC is a multi-entity real estate investor active in Kokomo, IN with 20 recorded acquisitions totaling approximately $7,873,265. Recorded purchases span 3 metros inside the same state footprint, which suggests a broader local-to-regional buy box. The most recent recorded purchase was in November 2025, so the visible activity window still looks fairly recent from a deed-record standpoint.

Recorded purchases skew toward Condo and Single Family Residential. Average observed purchase price sits near $393,663, which reads as mid-market acquisition pricing. Behavioral signals point to a noticeable resale or short-hold component and frequent private-lender financing within the recorded deed activity.

Observed window
March 2023 to November 2025

About 3 years of observed acquisition activity

Latest recorded purchase
November 2025

Recent enough to suggest the profile is still active

Market footprint
1 state / 3 metros

Spread across several metros inside the same state footprint

Strategy read
Private-lender active

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

20
Transactions
20
Properties
$7.87M
Total Volume
$393,663
Average Price

Property Types

CondoObserved
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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Goldsmith MartinMartino James

Who else does Goldsmith Martin fund?

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

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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 GAZ HOLDINGS LLC focus on?

Public records associated with GAZ HOLDINGS LLC show activity in Condo, Single Family Residential across Kokomo, IN.

How many properties are associated with GAZ HOLDINGS LLC?

Public records show approximately 20 properties and 20 recorded transactions associated with GAZ HOLDINGS LLC in this dataset.

Which lenders has GAZ HOLDINGS LLC worked with?

Recent recorded mortgage activity references Goldsmith Martin, Martino James. Full lender history is available in SFR Analytics.

How recent is GAZ HOLDINGS LLC's activity?

Records show activity from 2023 through 2025, with the most recent observed purchase recorded in November 2025.

Where is GAZ HOLDINGS LLC active?

Recorded activity is concentrated in Kokomo, IN, with footprint across 1 state and 3 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.