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# How Current Is Your Data?

## Overview

At Repliers, we understand that having access to the most up-to-date real estate information is crucial for your success. This article explains how we keep our data current and what you can expect in terms of data freshness.

## Our Data Update Process

We maintain current data through direct integration with MLS® Systems. Here's how our system works:

**Update Frequency**: Our system automatically checks for updates every 15 minutes, around the clock. This includes:

* New property listings
* Updates to existing listings (price changes, status updates, description modifications, etc.)
* Removed or expired listings

**Direct **MLS®** Integration**: We connect directly with MLS® Systems rather than relying on third-party data aggregators, ensuring we receive information as quickly as possible from the source and that we can address any issues or inconsistencies ourselves, if needed.

## Expected Data Latency

While we check for updates every 15 minutes, the actual time between when a change occurs in the MLS® and when you see it reflected in Repliers typically ranges from **5 to 20 minutes**.

This variation depends on several factors:

* The specific MLS® System processing time
* The timing of when the update occurs relative to our 15-minute check cycle
* Network connectivity and system load

## What This Means for You

With updates occurring every 15 minutes and typical latency of 5-20 minutes, you can be confident that:

* You're seeing near real-time market data
* New opportunities are identified quickly
* Price changes and status updates are reflected promptly
* You're working with some of the freshest real estate data available

# What questions does this article answer?

* How frequently does Repliers update MLS® listing data?  
* How “fresh” are new listings, price changes, status updates, etc.?  
* What’s the typical latency between an MLS® update and Repliers reflecting it?  
* How does Repliers keep data synchronized with multiple MLS® Systems?  
* Are there situations where data might appear stale and how should I handle them?