# The Realie Blog — Full Corpus (blog.realie.ai)

> Complete machine-readable corpus of all published engineering, property data API benchmark, and real estate market research articles from Realie Inc. (https://www.realie.ai).

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# Realie vs. ATTOM: Comparing Property Data APIs for Developers
- **Canonical URL**: https://blog.realie.ai/blog/realie-vs.-attom-comparing-property-data-apis-for-developers
- **Markdown URL**: https://blog.realie.ai/blog/realie-vs-attom-comparing-property-data-apis-for-developers.md
- **Published**: 2026-09-15
- **Topic**: Platform
- **Author**: Josh Dormody (Co-founder & CEO)
- **Summary**: Realie vs. ATTOM: a practical comparison of property data API latency, pricing, contracts, documentation, and data sourcing for developers in 2026.

ATTOM has been a major name in U.S. property data for years, with a broad offering across assessor, recorder, mortgage, foreclosure, valuation, and other real estate datasets.

Realie was built around a different model: self-service access, direct collection from public property-data sources, modern developer tooling, and infrastructure designed for low-latency API use.

One of the clearest differences between the two platforms is API performance, so we tested both using the same 100-property test set across 25 states.

## Realie vs. ATTOM API latency

For the ATTOM benchmark, we tested the **/property/basicprofile** endpoint across **100 unique properties in 25 states**. Each property was queried once, the request order was randomized, a persistent HTTP session was used, and connection warm-up requests were excluded from the results.

ATTOM successfully returned a property for all **100 of 100 requests**, giving us a clean benchmark without failed or empty responses affecting the results.

We then ran the same 100-property test set through Realie.

| Benchmark metric | ATTOM | Realie |
| --- | --- | --- |
| Minimum latency | 108.5 ms | **12.6 ms** |
| Mean latency | 232.6 ms | **54.6 ms** |
| P90 latency | 325.0 ms | **75.4 ms** |

In this benchmark, Realie's mean response time was approximately **76.5% lower** than ATTOM's, while Realie's P90 latency was approximately **76.8% lower**.

Another way to look at it: ATTOM's measured average response time was about **4.3× Realie's** during the test.

For developers building property data directly into search, underwriting, valuation, lead generation, or other user-facing workflows, that difference can be meaningful. Faster response times can reduce loading delays and lessen the need for additional caching or background processing to keep an application responsive.

These results represent our observed performance from a September 2026 benchmark. API latency can vary based on network conditions, infrastructure load, query type, geography, and other factors.

[Realie's address lookup documentation](https://docs.realie.ai/api-reference/v3/address-lookup) covers the endpoint used for low-latency property lookups.

## We also tested several other ATTOM endpoints

The broader ATTOM test included several additional endpoints using the same Denver property, with 20 measured requests per endpoint.

Average latency varied by endpoint:

- Assessment Detail: **131.8 ms**
- Sales History Snapshot: **143.4 ms**
- Sales Detail: **196.6 ms**
- AVM Snapshot: **186.1 ms**

The larger differences appeared in tail latency. During those tests, Sales Detail reached **579.6 ms** on its slowest request, while AVM Snapshot reached **957.2 ms**.

Because those endpoint tests used only 20 measured requests each, they are best treated as directional rather than as definitive P95 or P99 performance measurements. What they do show is that response times can vary meaningfully across ATTOM's different property-data endpoints.

## Developer experience: two different approaches

Performance is only one part of integrating a property-data API.

ATTOM's documentation is extensive and reflects a more **traditional enterprise documentation model**. Information is spread across the Developer Platform, API reference, guides, data dictionaries, and ATTOM Cloud help content. ATTOM also provides interactive documentation and code examples.

The main difference is organization and workflow. Compared with newer developer platforms, some information can take more navigation to locate, and the overall experience is geared more toward established enterprise users than rapid, self-service implementation.

Realie has taken a more modern, developer-first approach. Endpoint pages put request parameters and examples directly alongside the API reference, the documentation includes an **llms.txt** index for AI development tools, and Realie provides both a CLI and code-reference resources for common integration tasks.

For teams building with Cursor, Claude Code, ChatGPT, VS Code, and other AI-assisted development environments, that kind of structure can make integration faster and easier to navigate.

## Pricing and contract structure

The commercial model is another substantial difference.

In a March 17, 2026 email from ATTOM Data Solutions that we received, ATTOM described its API as an **annual contract** and provided the following monthly pricing:

| Monthly API calls | Price quoted |
| --- | --- |
| 5,000 | $600/month |
| 10,000 | $1,000/month |
| 15,000 | $1,350/month |
| 25,000 | $1,500/month |
| 50,000 | $2,000/month |
| 100,000 | $2,500/month |

For context, the pricing above reflects the rates ATTOM quoted in that March 2026 email and may not represent the pricing every customer receives today. ATTOM also notes on its developer site that pricing can vary based on usage and customer needs, with higher-volume requirements typically handled through enterprise plans.

Realie takes a more self-service approach. Pricing is published publicly, plans are month-to-month, and standard API access does not require an annual commitment. [See Realie's pricing](https://www.realie.ai/pricing).

That difference can matter most for startups and smaller teams. A company with a predictable, established data workload may be comfortable with an annual enterprise agreement, while an earlier-stage company may prefer the flexibility to start at a lower monthly tier, validate a use case, and scale usage over time without committing to a long-term contract.

Both models can make sense depending on the buyer. The main difference is that ATTOM is structured more like a traditional enterprise data provider, while Realie is designed to make it easier to start small and scale as usage grows.

## Where does the underlying property data come from?

ATTOM describes its database as **multi-sourced**, combining public records with proprietary and third-party data. [ATTOM discusses its sourcing approach here](https://www.attomdata.com/news/company-news/data-solutions/why-trust-matters-in-property-data-navigating-a-market-full-of-new-and-unproven-sources/).

Realie takes a more direct-source approach. We collect and normalize property data from county assessor, recorder, and other public-record systems, and where counties require paid access or data agreements, we work directly with those sources. [Read more about Realie's data platform](https://docs.realie.ai/introduction).

That difference matters operationally. When we find a problem with a field, county format, or source record, our team can trace it back to the underlying source and update the ingestion logic directly.

No property dataset is perfect, and county records themselves can be inconsistent or delayed. But Realie is designed to keep the path between the original public record and the API as direct as possible.

## So which model makes sense?

ATTOM is built as a traditional enterprise property-data platform, with broad datasets, specialized products, and multiple delivery options.

Realie is built for teams that want to get started quickly. Developers can create an account, get an API key, test the data, and scale usage without beginning with a large annual contract.

Performance is part of that difference. In our September 2026 benchmark using the **same 100-property test set**, ATTOM's Basic Profile endpoint averaged **232.6 ms**, while Realie averaged **54.6 ms**.

Realie is built around **fast API response times, self-service pricing, modern developer tooling, and direct-source data collection**. For teams that value those things, that is the experience Realie is designed to provide.

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# Best Property Data API for AI Companies in 2026
- **Canonical URL**: https://blog.realie.ai/blog/best-property-data-api-for-ai-companies-in-2026
- **Markdown URL**: https://blog.realie.ai/blog/best-property-data-api-for-ai-companies-in-2026.md
- **Published**: 2026-09-08
- **Topic**: Platform
- **Author**: Josh Dormody (Co-founder & CEO)
- **Summary**: AI applications need more than powerful models—they need reliable real-world data. Realie gives AI companies nationwide parcel, ownership, mortgage, tax, zoning, and property data through one developer-friendly API.

AI companies are increasingly building tools for real estate research, underwriting, investment analysis, lead generation, and automated property intelligence.

The challenge is that U.S. property data is fragmented across thousands of counties, assessors, recorders, and GIS systems.

Realie solves that by providing normalized nationwide property data through both an API and bulk data delivery.

## Why AI Companies Need Property Data

AI agents and LLM applications are good at reasoning, but they still need accurate structured data.

For real estate applications, that often includes:

- Property characteristics
- Parcel polygons
- Ownership data
- Mortgage data
- Sales and transfer history
- Property taxes
- Zoning
- Geospatial data

Realie combines these datasets into a standardized nationwide property record.

## One API for Nationwide Property Data

Instead of integrating with thousands of local government systems, developers can access property data through a single API.

This is especially useful for AI startups that want to focus on building their product instead of maintaining complex real estate data pipelines.

Realie can also sit directly behind an AI agent.

For example:

> “Find properties owned by this company and identify which ones have the most mortgage debt.”

The AI application can query Realie for ownership, mortgage, parcel, and property information, then use an LLM to analyze the results.

## API and Bulk Property Data

One major advantage of Realie is that companies are not limited to API access.

Realie also provides **bulk property data**, including statewide, regional, and nationwide datasets.

That is especially valuable for AI companies building:

- RAG systems
- Machine learning models
- Internal data warehouses
- Large-scale property enrichment
- Vector databases
- Analytics platforms
- Training and inference pipelines

An early-stage AI company might start with the API for live lookups and testing, then move to bulk delivery when it needs millions of property records inside its own infrastructure.

This gives teams flexibility to use the same property-data provider as they scale.

## Built for AI Startups

AI startups already spend heavily on inference, cloud infrastructure, embeddings, and model access.

Realie allows developers to start with self-service API access instead of committing immediately to a large enterprise property-data contract.

As the company grows, it can move into higher-volume API usage or bulk data delivery.

## Property Data Is Becoming AI Infrastructure

As AI models become more capable, competitive advantage is increasingly shifting toward access to high-quality real-world data.

For real estate AI, property data is a foundational layer.

Realie gives AI companies access to nationwide parcel, ownership, mortgage, tax, transaction, zoning, and geospatial data through both **API and bulk delivery**, without requiring them to build a nationwide property database themselves.

**For AI startups, AI agents, and real estate applications, Realie is one of the strongest property data platforms to build on in 2026.**

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# Best Property Data APIs in 2026: Top 6 Compared
- **Canonical URL**: https://blog.realie.ai/blog/best-property-data-apis-in-2026-top-6-compared
- **Markdown URL**: https://blog.realie.ai/blog/best-property-data-apis-in-2026-top-6-compared.md
- **Published**: 2026-09-07
- **Topic**: Market
- **Author**: Josh Dormody (Co-founder & CEO)
- **Summary**: Compare the best property data APIs for 2026, including Realie, ATTOM, Regrid, RentCast, LightBox, and Cotality. See how they compare on coverage, parcel data, mortgage information, pricing, and developer access—and why Realie stands out as the best overall option.

Choosing the best property data API in 2026 depends on what you are building.

Some APIs specialize in parcel boundaries. Others focus on rental estimates, mortgage data, listings, or enterprise real estate intelligence. The best option for most developers is the one that combines broad nationwide coverage, strong property-level data, transparent pricing, and an API that is easy to start using.

We compared six of the leading real estate and property data APIs for 2026.

## Best Property Data APIs for 2026

| Provider | Best For | Parcel Polygons | Mortgage Data | Self-Service Pricing |
| --- | --- | --- | --- | --- |
| **Realie** | **Best overall property data API** | Yes | Yes | **Yes** |
| ATTOM | Enterprise property intelligence | Yes | Yes | Limited |
| Regrid | Parcel maps and GIS | Yes | Limited | Yes |
| RentCast | Rental and residential analytics | No parcel polygons | Limited / not a core dataset | Yes |
| LightBox | Enterprise location intelligence | Yes | Yes | Mostly sales-led |
| Cotality | Mortgage and institutional data | Yes | Yes | Mostly sales-led |

## 1. Realie — Best Overall Property Data API

**Best for:** PropTech companies, AI applications, real estate SaaS, investors, lenders, developers, and data teams.

Realie is our pick for the best property data API in 2026 because it combines the breadth of a traditional enterprise property-data provider with the accessibility of a modern self-service API.

Realie provides nationwide property data covering more than 160 million U.S. properties across all 50 states and over 3,100 counties.

Available data includes:

- Parcel and assessor information
- Parcel boundary polygons
- Property characteristics
- Owner information
- Mortgage data
- Property taxes
- Sales and transfer history
- Zoning and land use
- Geographic coordinates
- Comparable properties

Realie also supports property searches by address, parcel ID, owner name, and geographic location.

One of the biggest advantages is pricing. Developers can start for free and move into paid plans beginning at $50 per month, without signing a long-term contract.

Realie's higher self-service tiers also make high-volume usage substantially less expensive than many legacy providers.

This makes Realie particularly attractive for startups and software companies that want enterprise-quality property data without committing to an enterprise contract before validating their product.

**Best overall property data API for 2026.**

## 2. ATTOM — Best for Enterprise Property Data

ATTOM is one of the most established property-data providers in the U.S.

Its datasets include property characteristics, ownership, mortgage records, sales history, foreclosures, valuations, and other real estate intelligence.

ATTOM is a strong option for large enterprises that need deep historical and specialty datasets.

The biggest downside is cost and contracting.

In pricing ATTOM distributed to its email list in March 2026, API plans included:

- 5,000 monthly calls — $600/month
- 10,000 calls — $1,000/month
- 15,000 calls — $1,350/month
- 25,000 calls — $1,500/month
- 50,000 calls — $2,500/month
- 100,000 calls — $2,500/month

ATTOM also stated that its API requires an **annual contract**.

That makes ATTOM considerably more expensive and less flexible for startups or development teams that simply want to begin testing an API.

ATTOM remains an excellent enterprise dataset, but Realie offers a significantly lower barrier to entry for most developers.

**Best for:** Large companies that need specialized enterprise property datasets.

## 3. Regrid — Best Parcel Data API for GIS

Regrid is one of the strongest APIs for parcel boundaries and geospatial property data.

Its platform covers more than 160 million U.S. parcels and is particularly well suited for GIS applications, land intelligence, mapping, site selection, and parcel visualization.

Regrid supports parcel searches using addresses, owners, parcel numbers, coordinates, polygons, and other geographic queries.

If parcel geometry is the primary focus of your application, Regrid is one of the strongest alternatives to Realie.

Where Realie has an advantage is combining parcel polygons with broader property intelligence such as mortgage, ownership, transaction, tax, and assessor data in the same API.

**Best for:** GIS applications, mapping platforms, and land-focused products.

## 4. RentCast — Best for Rental and Residential Data

RentCast is a popular developer-friendly real estate API focused heavily on residential property and rental analytics.

Its strengths include:

- Rental estimates
- Property valuations
- Sale comparables
- Rental comparables
- Property listings
- Residential property records
- Market statistics

RentCast also offers transparent monthly pricing and is easy for developers to get started with.

The main limitation is dataset breadth.

RentCast does not currently expose parcel-boundary polygons as part of its standard property data API, and mortgage data is much more limited than what is available from providers such as Realie, ATTOM, or Cotality.

RentCast also focuses primarily on residential properties, making it less suitable for applications requiring broad commercial, agricultural, vacant-land, or parcel-level coverage.

For rental-property analytics, however, RentCast remains an excellent choice.

**Best for:** Rental platforms, residential investors, AVMs, and comps.

## 5. LightBox — Best for Enterprise Location Intelligence

LightBox is a major real estate and location-intelligence provider with strong parcel, commercial real estate, zoning, property, and geospatial datasets.

It is particularly well suited for:

- Commercial real estate
- Site selection
- Parcel mapping
- Zoning
- Land-use analysis
- Enterprise GIS

LightBox offers deep datasets, but its products are generally more enterprise-oriented and sales-led.

For companies that simply want to create an account and begin testing property data immediately, Realie offers a more accessible path.

**Best for:** Large commercial real estate and location-intelligence companies.

## 6. Cotality — Best for Mortgage Data

Cotality, formerly CoreLogic, operates one of the largest real estate data ecosystems in the U.S.

Its products cover property characteristics, ownership, mortgages, valuations, tax data, transaction history, climate risk, and other institutional real estate datasets.

Cotality is particularly strong in mortgage and financial-services applications.

The primary drawback for developers is accessibility. Cotality is largely built for banks, mortgage companies, insurers, and large institutional clients rather than startups looking for a simple self-service property API.

**Best for:** Banks, mortgage companies, insurers, and institutional real estate users.

## What Is the Best Property Data API in 2026?

The best API depends on your use case.

For parcel mapping and GIS, **Regrid** is excellent.

For rental analytics and residential valuations, **RentCast** is one of the strongest options.

For large institutional datasets, **ATTOM, LightBox, and Cotality** are all well-established providers.

But for companies that need a combination of:

- Nationwide property coverage
- Parcel polygons
- Ownership information
- Mortgage data
- Sales and transfer history
- Tax and assessor data
- Commercial and residential parcels
- Transparent pricing
- Self-service API access
- No required annual contract

**Realie offers one of the strongest overall combinations in the property data API market.**

## Why Realie Is Different

The traditional property-data industry was built around expensive enterprise contracts.

Realie was built around a different model: make nationwide property data available to developers and software companies without requiring them to negotiate a large data agreement before they can start building.

Developers can start with the Realie API for free, move into affordable monthly tiers as usage grows, and eventually transition into enterprise API or bulk-data licensing when needed.

That makes Realie particularly well suited for modern PropTech companies, AI applications, real estate platforms, land applications, underwriting tools, investment software, and other products that depend on property data.

**Start building with the Realie Property Data API.**

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# Exploring the Best U.S. Property Data APIs of 2026—and Their Drawbacks
- **Canonical URL**: https://blog.realie.ai/blog/exploring-the-best-u-s-property-data-apis-and-their-drawbacks
- **Markdown URL**: https://blog.realie.ai/blog/exploring-the-best-u-s-property-data-apis-and-their-drawbacks.md
- **Published**: 2026-01-02
- **Topic**: Market
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: There are many factors to think about when choosing the best property data API

With real estate more data-driven than ever, a solid property data API can make or break your project. Whether you’re building an investor tool, analyzing market trends, or simply automating your own property lookups, you want reliable, affordable, and up-to-date data. Below, we’ll examine leading U.S. property data APIs of 2026 and note key drawbacks—often related to **pricing** or **data limitations**.

## 1. Realie

### Why Realie Stands Out

- **Cheaper Plans & Free Tier**: Realie offers significantly more affordable pricing than most alternatives, plus a free tier for those who want to test or handle smaller data volumes.
- **High-Volume Returns per Call**: Each call can return **up to 100 parcels**, saving on extra fees and reducing development complexities.
- **Modern UI & Easy Integration**: Built with a modern, intuitive interface that makes data easy to interpret and integrate.
- **Direct County Data**: Data is collected straight from counties, helping ensure accuracy and timeliness.

## 2. ATTOM Data Solutions

### Key Features

- Comprehensive nationwide coverage of tax, deed, mortgage, and foreclosure records.
- Neighborhood insights (demographics, crime, schools).
- AVM (automated valuation) estimates and analytics.

### Pricing Drawback

ATTOM is enterprise-oriented, and its pricing often reflects that. While it provides a massive dataset, smaller businesses or developers may find the cost prohibitive if they need continuous, large-scale data. Negotiating a contract can also be complex and time-consuming.

## 3. HouseCanary

### Key Features

- Automated Valuation Model (AVM).
- Rental estimates and risk analytics.
- Deep market forecasting and comparables.

### Pricing Drawback

HouseCanary is known for its sophisticated analytics—particularly valued by banks and mortgage lenders. However, licensing fees and analytics packages can get expensive, especially for small businesses or lean startups looking for a budget-friendly solution.

## 4. RentCast

### Key Features

- Rental data, including current market rent estimates.
- Historical rental listings and trends.
- Tools for rental comps and portfolio analysis.

### Drawback (Data & Polygons)

- **No Parcel Polygons**: If you’re looking for polygon/boundary data, you’ll have to look elsewhere.
- **Update Frequency**: Users have noted that data updates aren’t as frequent as some competitors, potentially resulting in slightly stale or incomplete information for fast-moving markets.

## 5. CoreLogic

### Key Features

- Large property database (assessor records, mortgages, liens).
- Advanced analytics and risk assessment solutions.
- Nationwide coverage.

### Pricing Drawback

CoreLogic is a major enterprise player, and cost can be a barrier for smaller teams. Their data is top-notch, but subscription fees and per-call costs can quickly exceed budgets, and access often requires larger upfront commitments.

## 6. Regrid

### Key Features

- Parcel boundaries and ownership details for over 150 million U.S. parcels.
- GIS-friendly data and mapping.
- Land-use and zoning info (select markets).

### Pricing Drawback

Regrid offers detailed GIS data, but **costs can escalate** if you need extensive coverage, advanced features, or heavy usage. Some developers also find specialized GIS data to be pricier because it’s more niche, requiring robust backend systems and licensing.

## 7. DataTree by First American

### Key Features

- County-recorded property documents, deeds, and public records.
- Historical and current ownership details.
- Nationwide coverage with premium-level detail.

### Pricing Drawback

DataTree’s direct-from-county approach is extremely reliable but often comes at a premium. Contracts can be complicated for smaller entities, and bulk data pulls can become expensive if you’re not doing enterprise-level volumes.

## 8. Zillow API (Evolving & Limited)

### Key Features (Historically)

- Zestimate” valuations.
- Comprehensive nationwide coverage of tax, deed, mortgage, and foreclosure records.
- Basic property and rental estimates (in the past).

### Drawback

Zillow has significantly **restricted its API** in recent years. It’s no longer open to the public like it once was, making it difficult or impossible for many third parties to tap into its data. This restricted access can hamper innovative use cases

## 9. Mashvisor

### Key Features

- Short-term rental data (including Airbnb).
- Rental income projections and ROI calculations.
- Neighborhood-level analytics.

### Pricing Drawback

While Mashvisor caters well to short-term rental analytics, its subscription costs can climb if you need broader coverage or deeper historical data. The platform’s specialized focus can also mean paying for analytics you may not need if you’re working outside the Airbnb or short-term rental model.

## Why Realie Might Be the Ideal Choice

1. **Affordability + Free Tier**Realie undercuts much of the market on price. The free tier makes it accessible for experimentation, demos, or smaller projects before committing to bigger usage.
2. **High-Volume Returns**Getting up to 100 parcels per call helps you do more with fewer API calls, which translates into fewer costs and simpler code.
3. **Modern UI & Simple Integration**Some legacy providers have clunky dashboards or outdated documentation. Realie’s user-friendly approach makes onboarding smoother.
4. **Direct County Data**Accuracy is paramount. By getting data directly from county sources, Realie cuts down on inconsistencies and delays found in some other solutions.
5. **Scalability**Whether you’re a startup or an established enterprise, Realie’s flexible pricing and robust infrastructure can grow with your needs.

## Final Thoughts

Selecting the right property data API often comes down to the balance of **quality, coverage, and cost**. Established names like ATTOM, CoreLogic, and DataTree offer comprehensive data but at higher price points and more complex contracts. Meanwhile, focused platforms like HouseCanary and Regrid deliver specialized analytics or GIS data that can also get expensive for larger-scale needs.

**RentCast** focuses on rental data but lacks parcel polygons and can have slower updates, which may not fit certain geospatial or real-time applications. **Zillow’s** once-open API is no longer as widely accessible, limiting options for many developers.

If you’re seeking **extensive property data** with **lower costs**, **generous free tiers, user-friendly tools**, and **up-to-date county records**, [**Realie**](https://www.realie.ai/real-estate-data-api) offers a compelling and modern alternative. It’s worth exploring—especially for teams looking to keep overhead low without sacrificing data accuracy or coverage.

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# Land Use vs. Zoning: What’s the Difference (and Why It Matters for Property Data)
- **Canonical URL**: https://blog.realie.ai/blog/land-use-vs.-zoning-what%E2%80%99s-the-difference
- **Markdown URL**: https://blog.realie.ai/blog/land-use-vs-zoning-what-s-the-difference.md
- **Published**: 2026-01-01
- **Topic**: Research
- **Author**: Josh Dormody (Co-founder & CEO)
- **Summary**: Land use and zoning are often confused, but they mean different things. Land use describes how a property is classified today, while zoning defines what’s legally allowed. This guide breaks down the difference, why land use data is easier to source than zoning, and how Realie provides both.

If you’ve ever tried to answer a “simple” question like *“Can I build a duplex here?”* or *“What is this property used for?”* you’ve probably run into two similar-sounding terms that are **not** the same thing:

- **Land use** = what the property *is* (or is being used as)
- **Zoning** = what the property *is allowed* to be used as

That distinction is the difference between describing reality and describing the rules.

Below is a clear breakdown of land use vs. zoning, why land use data is typically easier to collect at scale, why zoning is harder, and how **Realie** gives you both.

## What is land use?

**Land use** describes the **actual use** of a parcel—how it’s currently categorized in practice (often for taxation, assessment, and records purposes). Common examples:

- Single-family residential
- Multifamily
- Retail
- Industrial
- Agricultural
- Vacant land

In property datasets, land use is typically represented by a **use classification** that comes from the assessor/recorder ecosystem and helps governments track property characteristics for valuation and taxation.

Realie exposes this as **useCode** (more on that below).

## What is zoning?

**Zoning** is a **legal designation** set by a local government (city/town/municipality) that governs what you’re allowed to do with the property. Zoning answers questions like:

- What types of uses are permitted here?
- How tall can a building be?
- What setbacks/lot coverage apply?
- Can I add an ADU?
- Is this mixed-use allowed?

Realie exposes zoning as **zoningCode** (for example: **RD-5**).

## Land use vs. zoning (quick comparison)

**Land use (what is happening)**

- Describes the property’s **current** category/use
- Usually tied to **assessment/tax** systems
- Often more consistent to pull at scale

**Zoning (what is allowed)**

- Describes the **rules** for what *can* happen
- Defined by **local municipal code** and planning departments
- Frequently requires jurisdiction-specific lookup and interpretation

A property can also have *mismatches*:

- A building might be used as a duplex (land use) but zoned for single-family (zoning), meaning it could be **nonconforming** or grandfathered.
- A parcel might be zoned mixed-use but currently used as a parking lot.

## Why land use is usually easier for property data companies to provide

In the U.S., land use classifications are often available through **county-level systems**, because counties are typically the backbone of:

- assessment/tax rolls
- parcel records
- standardized property characteristic reporting

So if you’re building nationwide property data, land use tends to be more scalable because you can source it from a county’s assessment framework and map it into a consistent structure.

Realie’s API even documents land-use-style **use codes** through its feature key reference.

## Why zoning is harder (and why it often requires municipality-level research)

Zoning is a different world.

Even inside a single county, you can have many independent zoning authorities:

- cities
- towns
- villages
- unincorporated county areas (sometimes with separate county zoning)
- special planning districts

And zoning information may live in completely different places depending on the jurisdiction:

- a municipal GIS portal
- a planning department PDF map
- a zoning ordinance document
- a parcel viewer with a zoning overlay
- internal planning datasets (not always publicly downloadable)

That means zoning often requires **municipality-by-municipality** work:

- locating the right source
- extracting the zoning label/code
- interpreting what the code means (because “R-1” in one city is not the same as “R-1” in another)

In other words: **land use is often county-available; zoning is often municipality-dependent.**

## How Realie provides both land use and zoning

Realie includes **land use** and **zoning** fields directly in the Property API response schema:

### Land use in Realie: useCode

Realie’s land use data is represented by **useCode**, documented as the parcel’s use code in the schema.

You can reference the code meanings here: [**Realie useCode field key reference**](https://docs.realie.ai/api-reference/feature-key#usecode).

**Is useCode normalized?**
Practically speaking, yes: Realie provides a **single, consistent code reference** (one lookup table of use codes → descriptions) so you don’t have to maintain your own county-by-county decoding layer. The docs explicitly position the feature key as the translation layer from coded fields (like use codes) into readable descriptions. 
*(If you want to be ultra-precise in wording for the blog: call it “standardized” or “mapped into a consistent Realie taxonomy,” since the docs show one unified reference list.)*

### Zoning in Realie: zoningCode (+ jurisdiction)

Realie also returns **zoningCode** (example: RD-5) under land details & zoning, and includes **jurisdiction** (example: “PLANO CITY”) to indicate the governing area.

That pairing matters because zoning is only meaningful in context of the jurisdiction that defines it.

## Why land use and zoning both matter when evaluating a property

Land use and zoning often get used interchangeably, but they answer two different questions you’ll want to know before you buy, build, renovate, or market a property:

- **Land use tells you what the property is today.** It’s how the parcel is currently classified (like single-family, multifamily, retail, industrial, vacant land, etc.).
- **Zoning tells you what the property is allowed to be.** It’s the local rulebook that determines what uses are permitted and what restrictions apply.

When you have **both** land use and zoning, you can make faster, more confident decisions, such as:

- **Spotting mismatches** between current use and allowed use (for example, a multifamily building on single-family zoning)
- **Finding redevelopment or value-add potential** (for example, a low-intensity use on zoning that allows higher density)
- **Understanding constraints before you spend money** (setbacks, height limits, permitted uses, overlays, etc. vary widely)
- **Comparing properties more accurately** by separating what’s *there now* from what’s *possible under the code*

In short: **land use describes the present; zoning defines the possibilities and limitations.** Knowing both reduces surprises and helps you evaluate upside and risk with a lot more clarity.

If you want, paste the paragraph before and after this section and I’ll rewrite it so it flows perfectly with your existing post (same tone, same headings).

## TL;DR

- **Land use** = current property use/classification (often easier to source at the **county** level)
- **Zoning** = legal rules (often requires **municipality-level** sourcing and interpretation)
- **Realie provides both**:**useCode** for land use (with a single documented code reference):**zoningCode** (and **jurisdiction**) for zoning context

If you want, I can also turn this into:

- a shorter “glossary-style” post for quick SEO wins,
- a more technical developer-focused version (with request/response examples),
- or a keyword-optimized outline targeting phrases like **“zoning data API,” “land use codes,” “property zoning dataset,”** etc.

================================================================================
# Breaking the Data Monopoly: How Realie is Disrupting the Property Data Industry
- **Canonical URL**: https://blog.realie.ai/blog/breaking-the-data-monopoly-how-realie-is-disrupting-the-property-data-industry
- **Markdown URL**: https://blog.realie.ai/blog/breaking-the-data-monopoly-how-realie-is-disrupting-the-property-data-industry.md
- **Published**: 2025-05-04
- **Topic**: Market
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: Realie uses AI to collect property data directly from public sources—faster, cheaper, and without the middlemen.

## Overview

In the dynamic world of real estate technology, access to accurate and comprehensive property data is paramount. Traditionally, many companies have relied on established data aggregators like CoreLogic to obtain this information. However, emerging platforms like [Realie](https://www.realie.ai/real-estate-data-api) are revolutionizing the landscape by leveraging artificial intelligence to collect and provide property data more efficiently and affordably.

## The Traditional Data Model: CoreLogic's Dominance

CoreLogic has long been a dominant player in the property data industry, offering extensive datasets covering property ownership, tax assessments, mortgage information, and more. Their data is utilized by various stakeholders, including real estate professionals, financial institutions, and government agencies. However, this dominance has not been without controversy.

In 2014, CoreLogic acquired DataQuick Information Systems, a move that raised antitrust concerns due to the potential reduction in competition within the national assessor and recorder bulk data market. To address these concerns, the Federal Trade Commission (FTC) mandated that CoreLogic provide certain datasets to RealtyTrac (now [ATTOM Data Solutions](https://www.attomdata.com/)) to maintain market competition. However, in 2018, the FTC found that CoreLogic had not fully complied with this agreement, leading to an extension of the data-sharing requirement until at least 2022. [Read the full article from HousingWire](https://www.housingwire.com/articles/42772-ftc-sanctions-corelogic-for-failing-to-comply-with-dataquick-acquisition-agreement/).

## The Cost Implications for Data Consumers

Companies like ATTOM Data Solutions, which rely on data from aggregators like CoreLogic, often face significant licensing fees. These costs can be substantial and are typically passed on to end-users, resulting in higher prices for access to property data. For startups, small businesses, or individual professionals, these expenses can be prohibitive, limiting access to crucial information needed for informed decision-making.

## Realie's Innovative Approach: AI-Powered Data Collection

Recognizing the limitations of traditional data sourcing methods, [Realie](https://www.realie.ai/real-estate-data-api) has adopted a novel approach by directly collecting property data from public sources using AI agents. This strategy eliminates the need for intermediaries, reducing overhead costs and enabling Realie to offer more affordable data solutions.

Realie's AI-powered platform aggregates data from local municipalities and public records, covering over 180 million parcels across the United States. The platform provides more than 100 data fields per property, including ownership details, tax assessments, zoning information, and more. By automating the data collection process, Realie ensures that the information is constantly updated and readily accessible through a low-latency API.

## The Benefits of Realie's Model

- **Cost-Effectiveness**: By bypassing traditional data aggregators, Realie can offer competitive pricing, making property data more accessible to a broader audience.
- **Up-to-Date Information**: Realie's AI agents continuously gather and update data, ensuring users have access to the most current property information available.
- **Comprehensive Coverage**: With data on over 180 million parcels, Realie provides extensive coverage, catering to various needs within the real estate industry.
- **User-Friendly Access**: The platform's low-latency API allows for seamless integration into existing systems, facilitating easy access to property data for developers and professionals alike.

## Conclusion

The real estate data industry is undergoing a transformation, with innovative companies like [Realie](https://www.realie.ai/real-estate-data-api) challenging traditional models by leveraging technology to provide more efficient and affordable solutions. As the demand for accessible and up-to-date property information continues to grow, embracing such innovations will be crucial for professionals seeking to stay ahead in the competitive real estate landscape.

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# Comparing Property Data API Latency: Realie, RentCast, and ATTOM
- **Canonical URL**: https://blog.realie.ai/blog/comparing-property-data-api-latency-realie-rentcast-and-attom
- **Markdown URL**: https://blog.realie.ai/blog/comparing-property-data-api-latency-realie-rentcast-and-attom.md
- **Published**: 2025-04-26
- **Topic**: Platform
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: Review response times for Realie (9.49 ms), RentCast (439 ms), and ATTOM (441 ms), and see how sub-10 ms vs. ~440 ms latencies impact both bulk data workflows and real-time user experiences.

## Intro

In today’s data-driven environment, real estate applications depend on low API latency to differentiate between a smooth user experience and a sluggish interface. This post compares average response times for three popular property data APIs, [Realie](https://www.realie.ai/real-estate-data-api), [RealEstateAPI (REAPI)](https://www.realestateapi.com/), [RentCast](https://www.rentcast.io/), and [ATTOM](https://www.attomdata.com), and explains what those differences mean in practice.

## Latency Benchmark Overview

We ran a consistent latency test across all three APIs under similar network conditions. The average response times were:

- **Realie:** 9.49 ms
- **RealEstateAPI (REAPI):** 122 ms (P95)
- **RentCast:** 439 ms
- **ATTOM:** 441 ms

*Figure 1: a bar chart illustrating the gap between sub-10 ms responses and those that approach half a second:*

## Live Dashboard Metrics

To verify these benchmarked figures, we pulled each provider’s own reported metrics directly from their dashboards on April 16, 2025.

#### RentCast API Metrics

- **Average latency:** 439 ms
- **Maximum observed latency:** 7184 ms

*Figure 2: RentCast’s dashboard confirms an average response time of just under half a second, with spikes up to ~7 s.*

#### ATTOM API Status

- **Average response time (7-day avg):** 441 ms
- **Uptime (7-day avg):** 99.5 %

*Figure 3: ATTOM’s status page shows consistent sub-500 ms averages alongside high availability.\*

#### RealEstateAPI Metrics

- **P95 latency (7-day avg):** 122 ms (P50 Latency not displayed)

*Figure 4: RealEstateAPI P95 latency of 122 ms. (P50 Latency not displayed)*

#### Realie API Metrics

- **Average latency:** 9.49 ms

*Figure 5: Realie’s log showing average latency sub-10 ms.*

## What the Numbers Mean

#### For High-Volume Data Workloads

- **Throughput:**Fetching 100 records sequentially takes **under 1 s** with Realie,**~12 s** with REAPI**~44 s** with RentCast or ATTOM.
- **Infrastructure simplicity:**At ~10 ms per call, single-threaded, request-response code suffices;Around ~400 ms, you often need parallelism, batching, or caching to maintain performance

#### For Interactive, Customer-Facing Apps

**User perception:**

- Interactions under **0.1 s** feel instantaneous;
- Delays above **1 s** break a user’s flow.
- Realie’s ~0.01 s sits well below the “instant” threshold;
- REAPI’s ~0.122 s and RentCast/ATTOM’s ~0.44 s approach the point where users will notice delays—especially as calls stack.

**Performance budget:**

- A 10 ms data fetch preserves headroom for additional processing;
- A 122–441 ms fetch consumes a large portion of the total response-time budget.

## Conclusion

- **Realie** delivers sub-10 ms average latency, enabling ultra-responsive integrations and workflows.
- **RealEstateAPI (REAPI)** operates at ~122 ms, which may suffice for many batch-oriented tasks but can introduce perceptible delays in real-time scenarios.
- **RentCast** and **ATTOM** both hover around ~440 ms on average, suitable for bulk jobs but slower for interactive use.

Latency is just one factor: data coverage, pricing, feature set, and reliability also play key roles. However, when raw speed is the priority, these benchmarks show response times can vary by over 40× between providers. Choose the API whose performance profile best matches your application’s needs.

================================================================================
# Academic Research Solutions Using Realie's Property Data
- **Canonical URL**: https://blog.realie.ai/blog/academic-research-solutions-using-realie-property-data
- **Markdown URL**: https://blog.realie.ai/blog/academic-research-solutions-using-realie-property-data.md
- **Published**: 2025-02-21
- **Topic**: Research
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: In the dynamic education sector, access to accurate property data is crucial for academic research and institutional planning. Realie's property data offers detailed insights that support decision-making, strategic planning, and enhancing student experiences, making it an invaluable resource for educational institutions.

## Introduction

In today's rapidly evolving education sector, academic institutions face numerous challenges, including data-driven decision-making, strategic planning, and enhancing student experiences. Access to accurate and comprehensive property data is crucial in addressing these challenges. Realie offers a powerful solution by providing detailed property insights that can significantly benefit educational institutions.

## The Importance of Property Data for Educational Institutions

Property data plays a vital role in various aspects of academic research and institutional planning. It helps in understanding community demographics, assessing regional trends, and making informed decisions about campus expansions, student housing, and community engagement. Realie's property data provides educational institutions with the tools they need to excel in these areas.

## Addressing Academic Challenges with Realie’s Property Data

[Realie’s](https://www.realie.ai/) property data offers several key features that address the unique challenges faced by educational institutions:

1. **Comprehensive Coverage**: Access to data covering over 180 million property parcels in the U.S., providing a broad perspective on regional and local trends.
2. **Accurate and Up-to-Date**: Data sourced from local municipalities and constantly updated ensures reliability and relevance.
3. **Advanced Analytics**: AI-powered insights help uncover patterns and trends that can inform strategic decisions.
4. **Custom Solutions**: Tailored data solutions meet the specific needs of academic institutions, from research to planning.

## Benefits and Opportunities

The use of [Realie's](https://www.realie.ai/) property data in the academic sector offers numerous benefits:

1. **Enhanced Research**: Accurate property data enriches research datasets, supporting studies and publications with detailed information.
2. **Improved Planning**: Insights into regional trends and demographic shifts aid in planning campus expansions, student housing, and community initiatives.
3. **Targeted Recruitment**: Analyzing neighborhood and demographic characteristics helps identify potential students and target areas for recruitment.
4. **Data Verification**: Verifying property and demographic data ensures the quality and accuracy of institutional information.

## Conclusion

Realie's property data is a valuable resource for educational institutions, providing the insights needed to navigate challenges and seize opportunities in the academic sector. By leveraging this data, institutions can enhance research, improve planning, and deliver better experiences for students and staff.

================================================================================
# Mortgage Industry Solutions with Realie Property Data
- **Canonical URL**: https://blog.realie.ai/blog/mortgage-industry-solutions-with-realie-property-data
- **Markdown URL**: https://blog.realie.ai/blog/mortgage-industry-solutions-with-realie-property-data.md
- **Published**: 2025-02-17
- **Topic**: Market
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: Realie offers comprehensive property data solutions tailored for the mortgage industry, providing essential insights for lead generation, market analytics, and risk assessment, while meeting the expectations of modern digital consumers

## Overview

In today's competitive mortgage industry, the need for accurate and reliable property data is more crucial than ever. At [Realie](https://www.realie.ai/), we understand this need and are committed to providing comprehensive property data solutions that empower mortgage professionals to make informed decisions.

## Realie's Comprehensive Data Solutions

[Realie's](https://www.realie.ai/) data services are designed to align with the needs of the mortgage industry, offering a range of solutions such as lead generation, market analytics, and property research. Our detailed property and neighborhood information enable mortgage professionals to target retention and acquisition efforts effectively, enhancing their borrower base and driving business growth.

## Enhancing Mortgage Processes

We recognize the importance of streamlining the mortgage application process. With Realie's data, you can pre-populate applications and simplify borrower pre-qualification, improving the overall borrower experience. Our data also supports underwriting and risk assessment, providing the necessary insights to evaluate property records and conduct thorough risk assessments.

## Realie's Competitive Edge

Realie's market analytics capabilities allow you to identify high-risk areas and evaluate potential risks, including regional climate risks. This information is invaluable for developing effective pricing strategies and managing portfolio risks. Additionally, our data can assist in recruiting top-performing loan officers and other professionals, ensuring you have the best team to drive your business forward.

## Meeting Modern Mortgage Expectations

Realie's property data solutions are designed to meet the expectations of modern mortgage consumers. We understand the shift towards a digital mortgage experience, emphasizing transparency, personalization, and efficiency. Our services provide the tools needed to offer a seamless and customized experience for digital natives entering the housing market.

## Real-World Applications

Realie's property data can be applied in various mortgage industry scenarios, from conducting thorough property research to providing essential information for appraisals and home valuation estimates. Our data verification processes ensure the accuracy of customer-provided data, supporting both the quoting phase and the underwriting process.

## Conclusion

In conclusion, [Realie's](https://www.realie.ai/) property data solutions offer a comprehensive suite of tools to support the mortgage industry. Whether you're looking to enhance lead generation, streamline application processes, or conduct thorough market analytics, Realie has the data you need to succeed. Explore Realie's services today and discover how we can help you achieve your mortgage industry goals.

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# Using Realie's Property Data for the Insurance Industry
- **Canonical URL**: https://blog.realie.ai/blog/using-realie-s-property-data-for-the-insurance-industry
- **Markdown URL**: https://blog.realie.ai/blog/using-realie-s-property-data-for-the-insurance-industry.md
- **Published**: 2025-02-15
- **Topic**: Market
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: Realie's property data provides valuable insights for the insurance industry, offering comprehensive coverage, advanced analytics, and custom solutions. Learn how insurers can benefit from accurate data for underwriting, claims processing, and customer satisfaction.

## Introduction

The insurance industry is constantly evolving, facing challenges such as increasing claims costs, climate change, and rising customer expectations. To navigate these challenges, insurance companies require accurate and comprehensive property data. Realie’s property data offers a powerful solution, providing detailed insights into over 180 million property parcels across the U.S. In this blog post, we’ll explore how Realie’s property data can be leveraged by insurance companies to enhance underwriting, risk management, and customer service.

## The Importance of Property Data for Insurance Companies

Property data plays a crucial role in the insurance industry, enabling companies to assess risk, determine premiums, and streamline claims processing. Accurate property data helps insurers make informed decisions, reduce fraud, and improve customer satisfaction. With Realie’s property data, insurance companies have access to a wealth of information that can be used to gain a competitive edge in the market.

## Addressing Industry Challenges with Realie’s Property Data

Realie’s property data addresses key challenges faced by the insurance industry:

1. **Comprehensive Coverage:** Realie’s data covers over 180 million property parcels, providing a comprehensive view of properties across the U.S.
2. **Accurate and Up-to-Date:** The data is sourced from local municipalities and is constantly updated, ensuring accuracy and relevance.
3. **Advanced Analytics:** Realie’s platform offers advanced analytics and AI-powered insights, enabling insurers to uncover patterns and trends.
4. **Custom Solutions:** Realie offers custom solutions for enterprise clients, allowing insurers to tailor the data to their specific needs.

## Benefits and Opportunities

By leveraging Realie’s property data, insurance companies can:

1. **Enhance Underwriting:** Access to detailed property data allows for more accurate risk assessment and premium determination.
2. **Improve Claims Processing:** Real-time data and analytics streamline claims processing, reducing costs and improving customer satisfaction.
3. **Mitigate Risk:** Advanced analytics help identify potential risks, allowing insurers to take proactive measures.
4. **Increase Customer Satisfaction:** Accurate data and efficient processes lead to better customer experiences and increased loyalty.

## Conclusion

Realie’s property data offers a powerful tool for insurance companies, providing the insights needed to navigate industry challenges and seize opportunities. By leveraging this data, insurers can enhance underwriting, improve claims processing, and deliver superior customer service. As the insurance industry continues to evolve, access to accurate and comprehensive property data will be essential for success.

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# Introducing Realie's Comparable Property Search API Endpoint
- **Canonical URL**: https://blog.realie.ai/blog/introducing-realie-comparable-property-search-api-endpoint
- **Markdown URL**: https://blog.realie.ai/blog/introducing-realie-comparable-property-search-api-endpoint.md
- **Published**: 2025-02-14
- **Topic**: Platform
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: The new Realie Comparable Property Search API endpoint simplifies finding comparable properties

## Realie's Comparable Property Search API Endpoint

We're excited to announce the launch of our new [Comparable Property Search API Endpoint](https://docs.realie.ai/api-reference/premium/premium-comparables-search), designed to help you find comparable properties based on location and specific property characteristics. This powerful tool enables you to refine your search with various parameters, ensuring you get the most relevant results for your needs.

## Key Features

- **Location-Based Search:** Specify the latitude and longitude of the target property to find comparables within a defined radius.
- **Customizable Parameters:** Filter results by square footage, number of bedrooms and bathrooms, property type, and price range.
- **Time Frame**: Look back up to 18 months to find comparable sales.
- **Flexible Results**: Retrieve up to 50 comparable properties per request.

## How to Use the API

To use the [Comparable Property Search API Endpoint](https://docs.realie.ai/api-reference/premium/premium-comparables-search), provide your API key in the `Authorization` header. Here is an example of a `GET` request in Python:

```python
import requests

url = "https://app.realie.ai/api/public/property/comparables/"
params = {
    "latitude": 38.8951,
    "longitude": -77.0364,
    "radius": 1.0,
    "bedsMin": 3,
    "timeframe": 12,
    "maxResults": 25,
}
headers = {"Authorization": "YOUR_API_KEY"}

response = requests.get(url, params=params, headers=headers, timeout=10)
data = response.json()
print(f"Found {len(data.get('comparables', []))} comparable properties")
```

Replace `YOUR_API_KEY` with your actual API key to authenticate your request. The response includes an array of comparable properties that match your criteria, along with metadata about the search.

## Response Structure

The API returns a JSON object with the following structure:

- **comparables:** An array of comparable properties found, including sale date, sale price, square footage, beds/baths, distance, and parcel identifiers.
- **metadata:** An object containing additional information such as the count of comparables and the search parameters used.

## Get Started Today

Start using the [Comparable Property Search API Endpoint](https://docs.realie.ai/api-reference/premium/premium-comparables-search) to enhance your property search and valuation workflows. With its flexible parameters and detailed results, you'll have the insights you need to make informed decisions.

As always, if you have any questions about [Realie](https://www.realie.ai/) or any requests, please reach out to support@realie.ai!

================================================================================
# The Power of the Realie Assistant
- **Canonical URL**: https://blog.realie.ai/blog/the-power-of-the-realie-assistant
- **Markdown URL**: https://blog.realie.ai/blog/the-power-of-the-realie-assistant.md
- **Published**: 2025-01-31
- **Topic**: Platform
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: Immediate answers powered by the most comprehensive property data

## How the Realie Assistant Works

The Realie Assistant has come a long way in the past year. Leveraging the power of 180 million parcels and over 9 billion data points, the Realie Assistant can quickly and effectively answer complex questions about any real estate market in the United States. The days of needing your strategy team to learn SQL and spend hours running complex queries are officially over.

From market trends to block-specific information, the assistant can:

1. Answer specific questions about a given property
2. Generate charts depicting historical data
3. Help you formulate investing strategies

> “The days of needing your strategy team to learn SQL and spend hours running complex queries are officially over.” — Alex Franzen, Co-founder & CTO

## Test Drive: Hyper-Local vs. County Market Analysis

Let’s say I own a single-family home in Northern Virginia; I purchased this home in 2020 and am considering selling it to purchase another home in the area. I’d like to know how the micro-market within a one-mile radius is performing compared to the broader county market.

1. **Micro-Market Radius Query:** Asking the assistant to chart average sale prices within a 1-mile radius of the subject parcel immediately surfaces localized appreciation trends.
2. **County-Wide Benchmark Comparison:** Comparing that 1-mile radius against the county-wide median shows whether the immediate neighborhood trades at a structural premium.
3. **Bedroom-Matched Cohort Filtering:** Filtering specifically to 3-bedroom single-family homes (matching our ~$1,000,000 subject property) isolates true comparable appreciation from new-construction mix shifts.
4. **10-Year Historical Trend Validation:** Extending the lookback window to 10 years confirms whether a single-year spike (such as 2020) is a temporary outlier or part of a sustained multi-year premium relative to the county.

## Try the Realie Assistant

We’re excited to see what you build and analyze with the assistant, and we’re continuously expanding its toolset across parcel boundaries, ownership records, tax assessments, and comparable sales.

The [Realie Assistant](https://www.realie.ai/) is available to try directly in the platform, and we’d love to hear your feedback and feature requests. Feel free to reach out on X at [@realie_alex](https://x.com/realie_alex).

================================================================================
# Property Data API Use Cases
- **Canonical URL**: https://blog.realie.ai/blog/property-api-use-cases
- **Markdown URL**: https://blog.realie.ai/blog/property-api-use-cases.md
- **Published**: 2025-01-28
- **Topic**: Platform
- **Author**: Josh Dormody (Co-founder & CEO)
- **Summary**: Use cases for the Realie Property Data API and why we built it

## Introduction

Hey everyone, Josh here with more exciting news from Realie—this time, we’re talking all about the newly minted [**Realie Property Data API**](https://www.realie.ai/real-estate-data-api)! Before we dive in, let me share a bit about **why** we built it. As software engineers, my co-founder and I were searching for high-quality property data at a reasonable price for our own projects. What did we find? Mostly high-cost options or questionable data quality. On top of that, the user interfaces felt stuck in the early 2000s—clunky, slow, and anything but intuitive.

That’s when we realized: if nobody else is going to build a fast, modern platform with reliable data at a lower cost, why not just do it ourselves? After months of late-night coding and refining, we’re proud to say we’ve got a solution we genuinely love using—one that’s both developer-friendly and packed with accurate, up-to-date property information.

So, **why another real estate API?** We’ve poured our engineering expertise into making Realie’s data comprehensive, accurate, and lightning-fast—all accessible through our serverless infrastructure. Whether you’re a real estate professional, investor, or a tech startup in proptech, our API supplies the critical information you need to navigate the market with confidence. Think property characteristics, ownership records, valuation estimates, and sale history—you name it. And just like our public API launch, you can expect the same snappy response times, automatic scaling, and cost-efficiency.

## What You Get with the Realie Property Data API

We built the Realie Property Data API with a single aim: **to help you make better, data-driven decisions.** Here’s a quick look at some of our core features:

1. **Address & Location Data:** Accurate street addresses, ZIP codes, and geospatial coordinates—ideal for pinpointing areas of interest or conducting neighborhood-level analysis.
2. **Building & Lot Details:** Instantly access square footage, bed/bath counts, and lot sizes—giving you the context to quickly determine a property’s value or potential ROI.
3. **Ownership & Tax History:** Stay informed on current and historical ownership details and property tax assessments, helping you better gauge long-term trends and financial risk.
4. **Valuation Estimates:** Automated Valuation Models (AVMs) for quick property worth estimates—perfect for professionals who need up-to-date market insights.
5. **Sale & Listing Records:** Tap into previous sale dates, prices, and local market fluctuations, so you can understand price trends and competitive property landscapes.

## Built on a Serverless Backbone

Our Property Data API rides on the same **serverless architecture** we introduced in our initial [public API release](https://blog.realie.ai/blog/realie-api-launch). Here’s why that matters:

- **Automatic Scaling:** Sudden traffic spikes? No problem. Our backend automatically provisions more compute resources to keep things running smoothly.
- **Low Latency:** With optimized databases handling complex queries, response times remain consistently fast.
- **Minimal Cold Starts:** Through careful infrastructure tuning, we’ve cut cold start times down significantly, delivering consistent performance for all your requests.

## Who Benefits?

### Real Estate Professionals

Quickly access property info to streamline listings and showings. Better data means more informed conversations with clients, enabling you to deliver precise recommendations and close deals faster.

### Lenders & Mortgage Underwriters

Confirm property tax records and ownership data in seconds. Automate checks to speed up approvals and reduce risk, helping clients secure loans more efficiently.

### Investors & Home Flippers

Evaluate properties before you buy. See historical sale prices, neighborhood comps, and estimated valuations to pinpoint profitable deals and maximize ROI.

### Tech Startups & Data Platforms

Build cutting-edge real estate apps or internal dashboards. From interactive heat maps to home valuation widgets, the possibilities are endless for improving user engagement and decision-making.

### Analytics & Reporting Platforms

Leverage comprehensive property data for in-depth market analysis, trend detection, and forecasting. Whether you’re building AI-driven tools for portfolio management or offering real-time reporting dashboards, our API provides the accurate, up-to-date information you need to deliver actionable insights.

### Utilities & Energy Providers

Determine resource consumption and infrastructure needs by analyzing building size, lot details, and neighborhood characteristics. Plan solar installations, forecast energy usage, and optimize distribution networks with the help of reliable property data.

### Insurance Underwriting

Combine historical tax data, building characteristics, and ownership information to accurately assess a property’s risk profile. Streamline policy quotes, improve underwriting accuracy, and reduce manual errors with real-time data from our API.

### Marketing & Lead Generation

Create targeted campaigns by filtering properties based on square footage, location, or demographic data. Pinpoint underserved markets or clients most likely to convert, and use predictive insights to stay ahead of the competition.

## Getting Started

1. **Sign Up for an API Key:** Head to our [API docs](https://docs.realie.ai/api-reference/v3/overview) and request your key. This is your portal to everything Realie has to offer.
2. **Explore Our Endpoints:** From ownership details to valuation estimates, pick the endpoints that help you deliver the most value to your customers and stakeholders.
3. **Build & Test:** Integrate the API into your internal dashboards or consumer-facing apps. Our documentation is comprehensive, with plenty of code snippets and best practices.
4. **Scale Up:** As your user base grows, our infrastructure scales automatically—no performance headaches or downtime.
5. **Send Feedback:** We love hearing your suggestions. If there’s a specific feature or data set you need, reach out and let us know!

## Final Thoughts

I’m incredibly proud of how far Realie has come. The [**Realie Property Data API**](https://www.realie.ai/real-estate-data-api) isn’t just a data feed; it’s a **powerful, developer-friendly toolkit** designed to help industry professionals and businesses excel in today’s data-driven world. With our modern platform, accurate property data, and serverless backbone, we’re confident you’ll find the insights you need to deliver real value—whether you’re advising a real estate client, planning a solar installation, or refining your underwriting process.

If you’ve been searching for a hassle-free way to integrate quality real estate data into your workflows, now is the perfect time to jump in. And for everyone else—stay tuned for more updates on analytics tools, portfolio insights, and future features that will continue to redefine property data management.

Josh Dormody, Co-founder & CEO

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# Introducing the Realie API
- **Canonical URL**: https://blog.realie.ai/blog/realie-api-launch
- **Markdown URL**: https://blog.realie.ai/blog/realie-api-launch.md
- **Published**: 2025-01-12
- **Topic**: Platform
- **Author**: Alex Franzen (Co-founder & CTO)
- **Summary**: Introducing Our Lightning-Fast API: Powered by the Latest Serverless Tech

Hey everyone, exciting news from the tech trenches here at Realie! I'm thrilled to announce that after months of hard work from our brilliant dev team (and quite a few late-night Red Bulls), we've just launched the first version of our public API. 🚀

Now, I know what some of you might be thinking - "Just what the world needs, another API!" 😉 But hear me out: we've put a ton of thought and cutting-edge tech into making this API insanely fast and effortlessly scalable.

## How we built it

The API is built on serverless function infrastructure, which allows for automatic scaling of computing resources based on incoming request volume. This serverless architecture enables significant cost savings (passed onto you, our lovely customers), while also ensuring the API gracefully handles any traffic spikes without any service interruptions.

In terms of performance, we've been extremely impressed with the low-latency responses enabled by this architecture and thoughtful database tuning. During internal benchmarking, we consistently observed average response times in the 100-200ms range, even for complex geospatial queries. This snappy performance ensures a positive and timely experience for API consumers.

We've also implemented optimizations to mitigate cold starts, a common challenge with serverless architectures where unused function instances are deprovisioned to save resources. Through a combination of thoughtful architectural decisions and infrastructure tuning, we've achieved minimal cold start times. API clients can expect requests to be served by pre-warmed function instances in the vast majority of cases.

## Final Thoughts

Of course, there's a ton more going on behind the scenes to keep this API purring. But I won't bore you with all the nerdy details (though if anyone wants to geek out about it, my Twitter DMs are always open [@realie_alex](https://x.com/realie_alex)).

The important thing is this: we now have an API that's fast as blazes, effortlessly handles whatever you can throw at it, and is an absolute joy to work with. I personally have been having an absolute blast using it during our analytics page work (my next blog post topic).

To get started, head on over to our spiffy new [API docs](https://docs.realie.ai) and snag your API key. As always, we can't wait to see what amazing things you all do with it, and reach out with any features you’d like us to add. Happy building! 🥳

Alex

Founder & CTO