---
title: Leveraging AI to Automate Data Extraction from Geo-tagged Images
description: Geo.Intelli is a GIS automation solution that is designed to enable leading mapping and location players to uplift their user experience with better navigation while also creating more business opportunities for them.
image: https://blog.movate.com/hubfs/shutterstock_1236664573.jpg
---

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# Leveraging AI to Automate Data Extraction from Geo-tagged Images

 by The CSS Corp Editorial Team 

 /  April 30, 2020

***CSS Corp is enabling leading mapping companies to accelerate POI extraction from geotagged images through AI-ML led automation***

While navigating using a mobile device, we often select a source and a destination that are well-known and frequently visited places, such as hotels, apartment complexes, tourist attractions, corporate offices, etc. In mapping parlance, these places are called **points of interest (POI).** Most location-based applications and services need accurate POI data to serve their users effectively. Among several ways to capture POI data, extracting it from geotagged images is one of the most popular. Geotagged images contain geographical metadata like latitude, longitude, and place names, etc.

![geospatial tagging ](https://blog.movate.com/hs-fs/hubfs/geospatial%20tagging%20.png?width=698&name=geospatial%20tagging%20.png)

However, mapping companies often find it challenging to get detailed [POI data](https://www.csscorp.com/services/geospatial-technology-services/data-processing-content-management/) generated from geotagged images accurately. Fierce competition in this field has created a demand for high quality and freshness of POI data. It necessitates using efficient processes that bring reality to the maps in real-time or as soon as possible.

[![Unlock your 30 min Complimentary Consulting Session](https://hubspot-no-cache-na2-prod.s3.amazonaws.com/cta/default/2673776/297343f2-c86f-459f-9803-28449dab17c5.png)](https://hubspot-cta-redirect-na2-prod.s3.amazonaws.com/cta/redirect/2673776/297343f2-c86f-459f-9803-28449dab17c5)

A leading mapping and location data platform provider was under immense pressure to scale their services and capture the market share rapidly. A critical component of their services was seamless POI extraction from field-collected geotagged images while maintaining quality and accuracy benchmarks. Done manually, this process can be tedious and time-consuming. CSS Corp was able to support them through rapid deployment of trained resources at scale, empowered with an assisted automation approach, that accelerated the time-to-market for their services. It leveraged its proprietary Geo.Intelli system which uses [artificial intelligence](https://www.csscorp.com/services/digital-transformation-consulting/cognitive-customer-experience-platform/) for automated extraction of POI data from geotagged images, resulting in faster and efficient processing.

Geo.Intelli is a smart GIS system that automates the geotag extraction for POI location from images and leverages [NLP](https://www.csscorp.com/allnews/conversational-ai-is-driving-the-next-generation/) to check the completeness of POI or address name. Its AI-ML based APIs automatically extract the relevant data from images, perform a quality check on images, and reject images that are blurred, non-geocoded, or in invalid format. To ensure high accuracy, the system automatically cross-validates the extracted data with reference source data like area, city, latitude, longitude, and ZIP Code. It also allows for multiple POI addition from a single image.

Certain assisted [automation](https://www.csscorp.com/solutions/automation/smart-automation-services/) processes in the system leverage agents’ expertise and oversight to deliver high-quality results, for example, automated image analyzer with configurable field attributes, automated text extraction for additional information, and automated translation/transliteration processes.

The system also enhances the team’s productivity with integrated editing and review workflows and progress dashboards for instant reviews and analytics. Once the system extracts the POI, various users like agents, team lead, and QA can edit, review and perform quality checks within the system as per the workflows set and see the project performance on customized dashboards. Geo.Intelli gives users multiple export options to download final POI files in the desired format.

The system continuously learns from its data and updates its algorithms to get better with every [data extraction](https://www.csscorp.com/services/geospatial-technology-services/data-processing-content-management/). Today, it can extract English text from images with an accuracy of over 94%. Speaking of benefits to the client, the ability to make faster decisions on key address attributes accelerated the team’s productivity by 25%. Automated quality checks on key fields safeguarded data quality and reduced editing scope by 60%. Overall, the combination of CSS Corp’s Geo.Intelli system and a highly skilled team improved the efficiency of POI processing by 22%, enabling the client to scale their services faster than the competition.

**Conclusion**

With [location-based services](https://www.csscorp.com/services/geospatial-technology-services/spatial-analytics-insights/) and applications becoming essential for every aspect of businesses, having complete and accurate real-time data in maps becomes crucial. Stiff competition to the top is prompting location services providers to look for ways to optimize and accelerate their processes by leveraging AI and automation. [CSS Corp’s](https://www.csscorp.com/industries/navigation-mapping/) Geo.Intelli is a GIS automation solution that is designed to enable leading mapping and location players to uplift their user experience with better navigation while also creating more business opportunities for them.

[![Unlock your 30 min Complimentary Consulting Session](https://hubspot-no-cache-na2-prod.s3.amazonaws.com/cta/default/2673776/297343f2-c86f-459f-9803-28449dab17c5.png)](https://hubspot-cta-redirect-na2-prod.s3.amazonaws.com/cta/redirect/2673776/297343f2-c86f-459f-9803-28449dab17c5)

[AI](https://blog.movate.com/topic/ai), [geospatial systems](https://blog.movate.com/topic/geospatial-systems), [location intelligence](https://blog.movate.com/topic/location-intelligence), [geospatial analytics](https://blog.movate.com/topic/geospatial-analytics), [location-based services (LBS)](https://blog.movate.com/topic/location-based-services-lbs), [3D spatial positioning](https://blog.movate.com/topic/3d-spatial-positioning), [location intelligence data](https://blog.movate.com/topic/location-intelligence-data), [geospatial data](https://blog.movate.com/topic/geospatial-data), [geo-tagging](https://blog.movate.com/topic/geo-tagging), [data extraction](https://blog.movate.com/topic/data-extraction)

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- [retail analytics (1)](https://blog.movate.com/topic/retail-analytics)
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- [system integrators (1)](https://blog.movate.com/topic/system-integrators)
- [talent retention (1)](https://blog.movate.com/topic/talent-retention)
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- [top tech trends this year (1)](https://blog.movate.com/topic/top-tech-trends-this-year)
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- [workforce trends in 2022 (1)](https://blog.movate.com/topic/workforce-trends-in-2022)
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