10 Best Property Data Providers in 2026: APIs, Coverage, Intelligence & Pricing Compared
Property data has stopped being a lookup and become decision infrastructure. We compared ten providers on how they deliver it: APIs, coverage, enrichment depth, provenance and what it costs to get started.
Ten years ago, “property data” meant a record you looked up after a decision was already half made: an owner name, a square footage, a last sale price. In 2026 the same records sit upstream of the decision. They set the opening number on a cash offer, steer a lender’s collateral review, decide which parcels a developer’s model even considers, and increasingly feed AI assistants that answer questions about a specific address.
That shift changes what “best” means. A provider with the biggest database is not automatically the right one if its answers arrive through four separate contracts, cannot say where a value came from, or quietly fill a blank field with an estimate. The questions that matter now are about infrastructure. How many decisions can one integration support? Can every field be traced to a source? What happens when the data does not exist?
We buy houses. Every offer Local Home Buyers USA makes starts with a query against public-record property data for the subject parcel, its comparable sales and its local market. How our offers are built is published step by step. That operating use is why we care about this market, and it is also the source of our conflict of interest, which we disclose above and explain below.
The best property data provider is the one whose answers you can trace, whose gaps you can see, and whose integration you only have to build once.
Methodology · An operator’s blueprint
How we evaluated: structure over volume
This is an editorial ranking written from an operator’s seat, not a lab benchmark. We reviewed each provider’s current official website, product pages, API documentation and published pricing in November 2026. We did not test data accuracy, measure field fill rates, interview customers or receive vendor briefings.
Why we start from our own operations. Because Local Home Buyers USA and PropData share ownership, we know one platform from the inside: what its responses look like, how it labels sources, and what it returns when a record does not exist. That experience is why this report weights the things a production buyer actually feels: whether a value can be traced, whether a missing field is marked as missing, and whether the data reaches the tools a team uses. We hold the other nine providers to the same questions, but we could answer them only from what each vendor publishes. Where a vendor’s documentation does not describe its provenance or gap behavior, we could not give credit for it. That is not evidence the behavior is absent.
Why we did not rank on record counts. The national providers here cite between 136 million and 169 million U.S. properties or parcels, and nearly all of it traces back to the same county assessor, recorder and GIS sources. Quoted on its own, raw volume is close to a vanity metric. It mostly reflects what a vendor chooses to count. So we evaluated structural integrity instead, in this order of weight:
Provenance taggingWhether each value or record says which source supplied it, so a number can be defended to a seller, a lender or a regulator.
Explicit gap markingWhether missing, unsupported or uncovered data comes back labeled as null or unavailable, rather than silently estimated or borrowed from another geography.
Protocol readinessSelf-serve REST access, clear documentation, and support for AI agents through the Model Context Protocol (MCP).
Integration depthHow many decision layers (identity, parcel, valuation, rent, market, risk, community) a buyer can reach through one contract, one key and one response format.
Specialty depthWhere a provider is clearly the strongest choice for a particular job, such as title research, parcel GIS or rental comps.
Commercial accessibilityPublished pricing, entry cost and whether a team can start without a sales cycle.
What this method cannot tell you
Structure is not accuracy. This report can tell you how each provider says its data is built and delivered. It cannot tell you which one has the most complete or correct records in your counties. Only a side-by-side test on your own addresses can do that, and our selection guide shows how to run one in an afternoon.
These priorities reflect what matters to an operator building decision workflows. A large lender pricing climate exposure across a national loan book would weight them differently and might reasonably rank Cotality first. A title company would start with DataTree. We name those cases in each evaluation and in our selection guide.
Why PropData ranks first
On the three structural criteria we weight most, PropData is the provider whose behavior we could confirm directly. In a live request during this review, the record carried a named county source, a match level and an explicit coverage status, and its documentation commits to returning unavailable attributes as null rather than estimates. It serves REST and an OAuth MCP server, and it assembles identity, assessor, market, rent, comps and community context into one enriched response. It is also our sister company, and the other vendors did not get the same live check. Weigh our ranking with both facts in mind. We have tried to state PropData’s limitations as plainly as anyone else’s.
Executive summary
The rankings at a glance
Find your starting point
Choose the job you need data for. We’ll highlight the providers built for it.
Rank reflects fit against our stated criteria, not overall company size or data quality. No provider paid for inclusion.
01Editorial choice
PropData by PropTechUSA.ai
Best for integrated property intelligence
166M+U.S. parcel records indexed in the API, across all 50 states
7 countriesProduction products in the U.S., Great Britain, New Zealand, Australia, Estonia, France and Spain
100+ fieldsAssembled in one Full Enrich request, billed as one request
REST + MCP20+ production routes and an OAuth MCP server for AI agents
PropData is a property intelligence API built around a simple idea: an application should be able to resolve a property once and get back everything it needs to make a decision, with each layer labeled by source. It indexes 166M+ U.S. parcel records in its API and runs production country products in six more countries. Across that network it reports 400M+ property and parcel records and 7B+ normalized data points.
In practice, a single /v1/property request with enrich=full can assemble 100+ fields: assessor attributes, parcel context, market and rent signals, risk context and two census-geography community layers (census tract and block group), all attached to the core property record. PropData bills that as one request, however many layers it assembles. For a team that would otherwise license records from one vendor, rents from another and demographics from a third, that is the core argument: one integration, one response format, one bill.
No other provider on this list combines all three of these: self-serve keys with published pricing, REST and MCP access, and production data products in seven countries. The economics stand out too. PropData’s $79 Starter plan includes 10,000 requests a month, about 10 times the allowance of the nearest comparably priced published plan in this report (RentCast’s $74 Foundation tier, 1,000 requests). Beyond the property record, its documented routes cover comparable sales, value estimates, ZIP-level intelligence with FEMA flood context, natural-hazard risk across 18 hazard types, mortgage intelligence, change feeds for monitoring and parcel geometry.
From an address to a decision
Property inputAddress, assessor parcel number with county FIPS, or a latitude/longitude coordinate
Parcel identityResolved to a canonical parcel ID, with a match level and parcel geometry where published
Source recordsAssessor and county GIS records, each tagged with its named source and coverage status
Enrichment layersComparable sales, estimates, market and rent intelligence, census tract and block-group community context
Decision-ready outputOne JSON response for REST clients or MCP tools, with missing fields listed rather than guessed
Architecture diagram for illustration. It shows how a request flows; it does not display live data.
Documented capabilities
Property & parcel lookup
Coordinate search
Parcel geometry
Assessor & county GIS records
Comparable sales
Value estimates
Natural-hazard risk (18 hazard types)
Mortgage intelligence
Market intelligence
Rent intelligence
Tract & block-group community data
FEMA flood & hazard context
Change feeds (delta)
Full Enrich
REST API
OAuth MCP (8 tools)
Bulk & custom delivery
EPA facility proximity: restoration staged
Strengths
Integration depth: identity, records, market, rent, comps and community context through one key and one enriched request.
Provenance: in a live request we made during this review, the record carried a named source (a county GIS dataset), a match level and an explicit coverage status.
Honest gaps: the documentation commits to returning unavailable attributes as explicit or null, not estimated or broadened to another geography.
Accessible pricing: self-serve plans from $79 a month for 10,000 requests, published on its site.
AI-ready: an OAuth MCP server with tools for property lookup, coordinate search, market comparison, comparable sales, rent estimates and neighborhood profiles.
Coverage notes
Field availability varies by county assessor, as PropData’s own documentation states; not every parcel carries every attribute.
Pre-foreclosure data is county-scoped (Harris County, Texas; Hillsborough County, Florida; Johnson County, Kansas), and the EPA facility-proximity layer is staged for restoration rather than live.
Commercially, PropData publishes four U.S. plans: Starter ($79 a month, 10,000 requests), Builder ($199, 50,000, which adds Full Enrich and community intelligence), Scale ($499, 250,000) and Enterprise ($1,499), with annual options and bulk, white-label and custom delivery by contract. Prices are as listed on its site in November 2026.
Explore the API documentation, coverage notes and plans, or try the free keyless open-data API first.
ATTOM is one of the most established names in U.S. property data, and for many teams it is the default starting point. It licenses assessor and tax records, deeds, mortgages, foreclosure filings, building permits, parcel and school-attendance boundaries and neighborhood data, and layers analytics such as an AVM, a rental AVM and comparable sales on top. Its homepage cites coverage of “160M+ U.S. properties.”
ATTOM’s strength is breadth of record types under one data model, delivered however an enterprise prefers: a REST API with lookups by address, APN, ATTOM ID or coordinate; bulk licensing; cloud delivery to Snowflake and Databricks; and, new in its lineup, an MCP server that it describes as working across AI providers that support the protocol. If the question is “who has the deed, the mortgage and the permit history for this property,” ATTOM is a strong answer. It ranks below PropData on our criteria mainly on commercial accessibility and integration packaging: pricing is not published beyond a free 30-day trial, and its own pages cite different record counts (its developer portal still says 150 million).
Strengths
Wide range of record types: tax, deed, mortgage, foreclosure, permits
Multiple delivery modes, including cloud data shares
MCP server for AI applications
Watch-outs
No public price list; record counts differ across ATTOM’s own pages; U.S. only.
Best fit
Portals, lenders, insurers and data teams that need nationwide record depth and can negotiate an enterprise license.
Best for institutional property and risk analytics
Cotality is the name CoreLogic adopted in a global rebrand announced in March 2025. It brings decades of institutional history in property records, valuation and hazard risk. The company describes U.S. property records spanning 50 years with 99.9% market coverage, operates in Australia and the U.K. as well, and sells analytics most data vendors do not: climate and natural-hazard risk models, the Cotality HPI, its Total Home Value AVM, and the Araya platform for market and portfolio insight. It also runs the Matrix MLS platform used by many multiple listing services.
For a national lender or insurer, that modeling depth is the point, and on a risk-first weighting Cotality would rank first. In October 2026 it published an MCP server page offering pre-built connections for Claude and Databricks and citing 500+ data elements available through it, though access is for authorized users of licensed Cotality data. It sits third on our list because its strengths are delivered through an enterprise relationship rather than a self-serve integration, with no published pricing.
Strengths
Hazard, climate and valuation models with long history
Multi-country presence (U.S., Australia, U.K.)
Data marketplaces on Snowflake, Databricks and Google Cloud
Watch-outs
Enterprise sales model; MCP requires an existing data license; pricing varies by region and is not published.
Best fit
Lenders, insurers, servicers and large investors pricing risk across portfolios.
RentCast earns its place by being the easiest serious API on this list to start with. It covers property records, value and rent estimates with comparables, active sale and rental listings, and market trends, across what it describes as more than 150 million properties with over 500,000 record updates daily. Its free web app is popular with landlords; its API is popular with developers building rental tools.
The pricing is fully published: a free Developer tier with 50 requests a month, then Foundation ($74 a month for 1,000 requests), Growth ($199 for 5,000) and Scale ($449 for 25,000), with per-request overage and enterprise plans above that. RentCast also offers an MCP server. The trade-off is scope: it is a residential and rental specialist, not a source for deeds, liens or deep parcel geometry. Per request, its tiers sit above PropData’s published allowances, while its rental listing coverage is its distinguishing strength.
Strengths
Transparent self-serve pricing with a free tier
Rent and value estimates with comparables
Active rental listings and market trends
Watch-outs
Small free allowance; residential focus; limited title and recorded-document depth.
Best fit
Landlords, small investors and developers prototyping rental or investment apps.
If your problem is literally “where are the lot lines,” Regrid is purpose-built for it. It sells standardized parcel boundaries with ownership, address and zoning attributes, which it describes as 160M+ parcel records across the United States and major Canadian provinces, plus matched building footprints, standardized zoning in major metro areas and optional daily ownership updates.
Delivery is unusually flexible for GIS teams: an API with tiles and asynchronous batch endpoints, bulk files in formats from Shapefile and FileGDB to GeoParquet, an Esri feature service and a field-ready Property App. Its MCP server answers schema and coverage questions without a token and bills live data per record returned. Two buyer notes from Regrid’s own materials: self-serve usage tops out around 10,000 records a month before enterprise licensing, and its terms require disabling AI model training and data sharing when its data is used with language models.
Strengths
Nationwide standardized parcel geometry
Building footprints and zoning layers
GIS-native delivery formats and batch API
Watch-outs
Parcel and land-record focus, not valuations or transactions; enterprise license above modest self-serve volumes.
Best fit
Utilities, renewables, telecom, government, site selection and any map-first application.
HouseCanary is a valuation company first. It offers AVMs and valuation reports, home and rent price indexes, forecasts up to 36 months out, portfolio monitoring and a real estate data API covering more than 75 data points at property, block, block-group, ZIP, metro and state levels. It cites a dataset of more than 136 million properties and says it serves single-family rental operators, mortgage lenders and whole-loan buyers.
Pricing is published and layered: Basic at $19 a month, Pro at $79 (which adds core API access) and Teams at $199, with enterprise plans above. API calls are priced per call, from roughly $0.30–$0.50 for basic endpoints up to $4–$6 for premium ones, depending on plan. That suits teams that need a defensible valuation on a specific asset more than teams enriching millions of records. It also offers CanaryAI, a generative AI assistant, though it does not advertise an MCP server.
Strengths
Valuation-grade AVMs and reports
Price indexes and multi-year forecasts
Published plan and per-call pricing
Watch-outs
Residential only; premium endpoints are expensive at volume; advanced APIs need Teams or Enterprise.
Best fit
Lenders, SFR operators, capital markets desks and investors underwriting individual assets.
Best for property prospecting and contact enrichment
BatchData pairs property data with people data. Alongside property lookup and search APIs, AVMs and comparables, it sells skip tracing, reverse skip tracing, phone and address verification, saved-search alerts and portfolio monitoring. It cites 169M+ parcels, 355M+ contact records and 156M+ building permits across more than 3,100 counties, and offers an MCP server with OAuth sign-in for AI assistants.
Its pricing is published but built for volume: property data plans start at $1,000 a month for 100,000 records, skip tracing runs from $2,000 a month, and add-ons such as comps and listings are priced separately. For an acquisitions team running outbound campaigns, that bundle is the product. Buyers should treat contact data with care: BatchData’s own MCP page notes that skip-trace matches on LLC- or trust-owned properties are not certified owners, and phone and email outreach carries consent and do-not-call obligations.
Strengths
Property search plus contact enrichment in one vendor
Large published record counts and permit data
Monitoring and buy-box tools
Watch-outs
Highest entry price among self-serve options; contact data brings compliance responsibilities.
Best fit
Investors, wholesalers, home-services marketers and proptech prospecting platforms.
DataTree is First American’s property research platform, and its distinguishing asset is what sits behind it: a title insurer’s archive of recorded land documents. First American presents DataTree as the place to search property records, retrieve recorded document images such as deeds and mortgages, and order property and title-chain reports, with pay-as-you-go and subscription options. The DataTree.com address now redirects to First American Data & Analytics.
That makes DataTree the specialist pick when the question is about the legal record itself: who conveyed what to whom, which liens were recorded, and what the actual instrument says. It ranks lower on our list because its center of gravity is a research product for professionals rather than a developer-first enrichment API. First American’s product pages did not allow automated retrieval during our review, so we have kept this description general. Confirm current coverage, API access and pricing directly with First American.
Strengths
Recorded document images from a title-industry archive
Title-chain and lien reporting
Backed by one of the largest U.S. title insurers
Watch-outs
Research-product orientation; API and bulk terms must be confirmed with First American.
Best fit
Title and escrow officers, real estate attorneys, lenders and investors doing pre-acquisition title review.
Best for commercial property and geospatial intelligence
LightBox is built for commercial real estate. Its core data asset, which it calls SmartFabric, links parcel boundaries, structures and addresses, and its APIs cover geocoding, parcels, addresses, assessments, structures and zoning across the U.S. and Canada. Its EDR line adds environmental due diligence, which it describes as 23 million environmental records, and applications such as LightBox Vision put nationwide property data on a map for brokers, lenders and appraisers.
That combination of parcel, structure, zoning and environmental context is what a CRE transaction team needs, and LightBox delivers it through APIs, GIS feature services, Snowflake and an MCP connector. It ranks ninth on our criteria because it is enterprise-oriented, does not publish U.S. parcel counts or prices, and is less of a fit for residential developers. For commercial diligence it belongs near the top of any shortlist.
Strengths
Parcel, structure and zoning data designed for CRE
Environmental due-diligence records through EDR
GIS, API, Snowflake and MCP delivery
Watch-outs
No public pricing or U.S. coverage counts; commercial focus.
Best fit
CRE lenders, brokers, appraisers, developers and environmental diligence teams.
Cherre solves a different problem from everyone else on this list. Rather than selling a property dataset, it connects an investment manager’s own systems (accounting, leasing, deal tools) and licensed third-party data into a standard data model and knowledge graph, then serves that through an API, warehouse egress to Snowflake, BigQuery, AWS or Azure, dashboards, and Agent STUDIO, its environment for building AI agents on connected data. RealPage completed its acquisition of Cherre on July 14, 2026; Cherre says it will remain an open hub for other vendors.
For a large owner juggling dozens of data feeds, Cherre can be the layer that makes the rest usable. Its value depends on the data a client already has or licenses, and it is sold through demos and enterprise contracts. That is why it closes our list: it is an essential category, but not a property data source in the sense the other nine are.
Strengths
Connectors, mapping and a standard real estate data model
Warehouse egress and API access across sources
AI agent tooling on connected data
Watch-outs
Integration platform rather than primary data; enterprise pricing; ownership change in 2026.
Best fit
Asset managers and investment managers consolidating internal and licensed data.
Published price tags are only the visible part of what property data costs. Across this market, four pricing models coexist, often within the same vendor:
Per requestA monthly allowance of API calls with overage, as with PropData and RentCast. Predictable for apps that look up one property at a time.
Per recordBilling by records returned, common for bulk exports, batch jobs and some MCP access, as with Regrid’s live MCP data.
Per call, priced by endpointPremium analytics cost more per call, as with HouseCanary’s valuation endpoints.
Enterprise licenseAnnual contracts scoped by geography, fields, use case and redistribution rights. Typical for ATTOM, Cotality, LightBox and Cherre.
The number that matters is cost per decision, not cost per call. If underwriting one property means calling a records API, a valuation API, a rent API and a demographics source, the real price is four requests, four contracts and four integrations to maintain, plus the engineering time to reconcile four identifiers for the same parcel. Enriched responses change that arithmetic. PropData counts a Full Enrich request as one unit regardless of how many layers it returns; other vendors bundle differently. When comparing quotes, price a realistic workflow end to end.
Read the license as carefully as the price. Contracts differ on whether you may display data to end users, cache it, combine it with other sources, or use it to train models. Regrid’s terms on AI model training are one visible example. A cheap feed that cannot legally power your product is not cheap.
Coverage
Coverage quality beats raw record counts
Look at the headline numbers in this report and something stands out: they cluster within about 25% of one another. BatchData cites 169M+ parcels, PropData 166M+ indexed parcels, ATTOM and Regrid 160M+, RentCast 150M+, HouseCanary 136M+. The U.S. has a finite number of parcels, and every serious national provider is drawing on largely the same public sources: county assessors, recorders and GIS offices. A difference of a few million records says more about what each vendor counts (parcels, properties, addresses, units) than about who has better data. Treated as a headline, record volume is a vanity metric.
What separates providers is everything a record count hides:
Field fill. A record with an address and an owner name is not the same as one with year built, living area, assessed value, last sale and geometry. Ask for fill rates by field and by county in your markets.
Freshness. How quickly does a recorded sale or a new assessment roll appear? Daily, monthly and annual update cycles all exist.
Provenance. Can the provider tell you which source supplied a value, and when? If you have to defend a number to a seller, a lender or a regulator, this matters more than any other attribute.
Gap behavior. When data is missing, does the response say so, or does it quietly substitute a modeled estimate or a neighboring geography? Silent fills are how bad decisions get made with confidence.
This is the lens behind our ranking. A provider that marks a county as uncovered is more useful than one that returns a plausible guess, because you can route around a known gap. Our coverage of how sellers should read automated estimates makes the same point from the homeowner’s side of the table.
Implications
What it means for investors, developers, lenders and homeowners
Investors
Speed matters, but traceability matters more when you are wiring money. Use an enriched source for screening and comps, a valuation specialist for the final number on larger deals, and recorded documents before closing. Be wary of any acquisition model whose inputs you cannot explain to a partner.
Developers and product teams
Every additional vendor is another schema, another key rotation, another failure mode. Start by mapping the decisions your product makes, then choose the fewest providers that cover them with provenance. MCP support is now a practical differentiator: PropData, ATTOM, Cotality, RentCast, Regrid, BatchData and LightBox all advertise MCP access, with very different scopes and billing.
Lenders and insurers
Model governance and auditability dominate. Documented AVM methodology, hazard models and long histories are why Cotality, HouseCanary and ATTOM are entrenched here. Integrated APIs fit best upstream, in prequalification, lead routing and portfolio monitoring.
Homeowners and sellers
You will rarely license these feeds yourself, but they shape the offers and estimates you receive. Ask anyone who prices your home which records they used and how recent they are. A credible buyer can show you the assessor record and the comparable sales behind an offer. Condition still matters: no dataset sees a failing roof or a renovated kitchen, which is why a data-driven number is a starting point, not a verdict. If you are weighing timing, our should-I-sell guide walks through the trade-offs.
Selection guide
How to choose a property data provider
List decisions, not datasets. “Price a cash offer in 60 seconds” implies identity, records, comps and market context. Write those down first.
Test your own addresses. Pull 50 to 100 properties from your real markets, including rural parcels and new construction, and compare responses field by field.
Check gap behavior. Request a parcel you know is unusual. See whether the provider flags uncertainty or invents certainty.
Price the workflow. Model a month of realistic usage, including enrichment calls, overages and the number of separate contracts.
Read the license. Confirm display, caching, redistribution and AI-use rights for your actual product.
Plan for two providers. Most mature stacks pair a broad integrated source with one specialist: a valuation model, a title archive or a parcel GIS layer.
If you want a single integrated starting point, start with PropData. If you are an ATTOM customer looking for alternatives, the closest substitutes depend on what you use ATTOM for: PropData or RentCast for developer-friendly enrichment and rent data, Regrid for parcel geometry, HouseCanary for valuations, and DataTree for recorded documents.
FAQ
Frequently asked questions
What is the best property data provider in 2026?
It depends on the job. On our criteria, which weight integration depth, provenance and developer access most heavily, PropData by PropTechUSA.ai ranks first. PropData shares ownership with Local Home Buyers USA. For institutional risk modeling, Cotality is the stronger choice; for recorded documents, First American DataTree; for parcel GIS, Regrid.
What is the best property data API for developers?
Developers usually value published pricing, clear documentation and self-serve keys. PropData and RentCast both publish plans and allow immediate sign-up, and HouseCanary publishes per-call API pricing. ATTOM offers a free 30-day trial. Choose based on whether you need integrated enrichment, rental data or valuations.
What are the best ATTOM alternatives?
The right alternative depends on which part of ATTOM you rely on. For broad enrichment with published pricing, consider PropData or RentCast. For parcel boundaries, Regrid. For valuations, HouseCanary. For deeds and recorded documents, DataTree. For institutional analytics, Cotality.
Are property records public data?
Most underlying facts, such as assessed values, recorded deeds and parcel boundaries, originate with county and municipal governments and are public records. Providers add value by collecting, standardizing, linking and updating them across thousands of jurisdictions, and their compiled databases are governed by license terms.
How much does a property data API cost?
Published entry prices in this report range from free developer tiers (RentCast’s 50 requests a month) to $79 a month (PropData Starter, 10,000 requests) to $1,000 a month (BatchData’s first property data plan). ATTOM, Cotality, LightBox and Cherre sell through quotes. Compare cost per complete decision, not per call.
Why didn’t you benchmark accuracy?
A meaningful accuracy benchmark needs thousands of addresses, verified ground truth and every vendor’s paid access under comparable terms, and the results would still vary by county and field. We chose not to publish numbers we had not measured. Instead we evaluated structure: provenance, gap marking and protocol readiness. We also recommend that buyers test 50 to 100 of their own addresses before signing. That limitation is real, and we would rather state it than hide it.
Do these providers cover every U.S. county?
Several state nationwide coverage, but field-level completeness always varies by county because local governments publish different attributes on different schedules. Ask any vendor for county-level fill rates in the markets you care about.
Which providers support MCP for AI assistants?
As of November 2026, PropData, ATTOM, Cotality, RentCast, Regrid, BatchData and LightBox advertise MCP servers or connectors. HouseCanary offers its own AI assistant, and Cherre offers an AI agent studio. Access, tool coverage and billing differ widely.
How does Local Home Buyers USA use property data?
Our offer process starts with public-record data on the specific parcel, its comparable sales and its local market, queried through PropData. We publish how offers are built so sellers can check the inputs.
Conclusion
Our verdict
The property data market in 2026 is not short of records. It is short of answers that can be traced, gaps that are labeled, and integrations that do not multiply with every new question. The established players earn their positions: ATTOM for breadth, Cotality for institutional risk, DataTree for the legal record, Regrid for the map, HouseCanary for valuation, LightBox for commercial diligence, Cherre for stitching it all together, RentCast and BatchData for the jobs they specialize in.
Our editorial choice is PropData because it is built around the problem we see every day: getting from an address to a defensible decision through one integration, with the source of every layer in view. We are not neutral about it, and we have told you why. Test it against your own addresses, alongside any provider on this list, and let the responses make the case.
Build on traceable property intelligence
PropData resolves a property, attaches source-labeled records and enrichment layers, and returns one response through REST or MCP. Self-serve plans start at $79 a month.
All provider facts were taken from the official pages below, reviewed November 8, 2026. Coverage figures are each vendor’s own claims; we did not verify them independently. PropData capabilities were also checked against its live API documentation and one live API request. First American’s product pages could not be retrieved automatically, so the DataTree description is limited to First American’s general published positioning.
Local Home Buyers USA is a direct buyer of residential real estate, not a licensed broker. Seller Intelligence is editorial commentary based on named sources and public data; it is not legal, tax or financial advice. Editorial standards.