Agent
Discoverability

ChatARV

Real estate comps and ARV

View in the ChatGPT registry
Brand
Unknown
Category
Pending
Primary Subcategory
Pending
Integration details

Description

ChatARV values residential real estate for investors, wholesalers and agents. Give it a US property address and it finds comparable recent sales, adjusts them against the subject property, and reports an after-repair value (ARV) with a confidence rating and the top comps with photos. With ChatARV in ChatGPT you can: - Run comps on an address, with optional square footage, beds, baths, property type and custom search instructions - Revise a report's comps with a different search radius, square footage range, property type or valuation method - List and open your saved comp reports - View photos of the subject property or any of its comps - Estimate repair costs by category from a description of the subject property's condition - Check your account details Limitations: ChatARV covers US properties only and requires a ChatARV account. Reports created in ChatGPT are saved to that account, and each comp run counts toward the account's monthly comp limit. A comp run usually takes 30 to 90 seconds.

Integration type
Plugin
Verification status
Not applicable
Platform
ChatGPT
Category
Pending

The broad Category that contains the Primary Subcategory.

Primary Subcategory
Pending

The Primary Subcategory used for this profile’s headline score.

Secondary Subcategories
None listed

Other Subcategories where the Integration is listed.

Brand
Unknown
Access
Account required
First tracked
2026-10-31
Tool count
8
Market
US
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Primary Subcategory

Competitive lineup

No Primary Subcategory assigned yetOnce ChatARV has a Primary Subcategory, the Plugins and Connectors it competes with will appear here with their scores.
Tools

8 tools agents can invoke

Recommended guideHow to get your ChatGPT Plugin suggestedFollow the practical steps agents use to find, shortlist, and choose your Plugin.Read guide
FAQs

ChatARV ChatGPT Plugin FAQ

How the directory, categories and Discoverability Score work.

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How do I improve ChatARV's ChatGPT Plugin discoverability?

The levers are the listing surface agents actually read: names, descriptions, keywords, tool metadata, and registry health. Which lever matters depends on where discovery breaks, which is what continuous measurement shows.

Where is this profile measured?

This profile uses the geography attached to the latest public registry snapshot: US. Locale tags are intentionally omitted.