Geographic and locational data—maps—are one of the most useful data types for contextualizing broader enterprise datasets. They turn static images of locations into multi-directional data that can be densely inter-woven with broader data assets.

In a wide variety of contexts—from a virtual tour guide to the shops in an indoor mall to a comprehensive map of urban businesses—maps provide a vital link between detailed data insight and ground-level human experience.

Maps contain an astonishing depth of information which necessitates a specialized skill set for analyzing the true complexity of location-rich data sets. This fact hinders far too many enterprises in their efforts to develop geography-rich data infrastructure.

A proven process and specialized tools are needed to efficiently capture this expansive intelligence at an enterprise scale.

Out-Innovate, Out-Compete and Out-Sell Your Competition


Unlocked location-rich data ranging from interior maps to city transit guides

Extensive annotation and contextualization centered on client-selected priorities

Proven management techniques, run by pros with experience in running enterprise-scale data pipelines across the globe

Best practices for quality control and monitoring baked in at every stage of collection and processing

Smart automation and pre-built pipeline templates enabling efficient handling of map-data even at a massive scale

Analysis of subtle geographic factors and background research for deep contextualization


Map Data Collection Services
  • Our specialists in location-rich data thoroughly analyze client data requirements
  • Our ML experts validate all relevant requirements
  • When required, we can help in the field measurement, scanning, and GPS work for original map generation
  • We are fully capable with maps ranging from consumer-facing to densely technical
  • Our full-service data annotation service seamlessly handles other data types embedded in maps
Maps Concepts and Prototypes
  • Annotation and labeling powered by Zen’s geography-savvy ML models
  • Pros with special training analyzing map data capable of analyzing even the subtlest characteristics
  • Ongoing process monitoring from quality specialists with experience managing large-scale data projects that handle volume without sacrificing precision
  • Background research to verify geographic data, from web to phone, to in-the-field
Map Insight Services
  • Thorough analysis including proximity, feature labeling, logical inference from listed features, and connections with broader data sets like location-tagged images
  • Real-time processing capabilities capable of supporting live mapping applications for various use-cases
  • High-quality data processing capable of serving as a foundation for geography-capable machine learning projects
  • Annotation on deep characteristics far beyond superficial categorization


Operational Analytics and Support

  • Real-time tracking and evaluation of asset movement
  • Automated routing services in support of key workflows or transportation networks
  • Integration of past map and location data repositories with contemporary data infrastructure
  • Geography-rich consulting services

Customer Service and Support

  • “Find a Location” services
  • Live customer-facing routing and mapping applications
  • Customer service delivery customized by locale
  • Consumer map-data cleaning and verification

Sales and Marketing

  • Geographic advertisement evaluation and targeting
  • Comparative analysis of branch locations, customer addresses, and other geography-centric data points
  • Live sales support based on current location and customer background
  • Automatic intake and integration of location-based customer requests

Machine Learning

  • Automated map data infrastructure
  • Tools capable of learning and mapping new locations automatically
  • Machine Learning tools familiar with live-location data
  • B2C and B2B-facing Map processing services


Fully digitized map data is everywhere. Ride-sharing, search, mass transportation, and logistics are just a few of the rapidly expanding use cases for map data that continue to define the global economy. Processing this data at scale means finding new methods for collecting and understanding essential elements of location-rich data sets — like two and three- dimensional proximity that is rarely encountered in other enterprise contexts.
What’s more? Many applications demand the capability to evaluate these factors in real time and use them to generate actionable feedback for consumer or enterprise users.

Building out the technical and personnel resources needed to establish this sort of geography-rich data pipeline can seem a Herculean task. At Zen3, we have put our data services “on the map” by supporting our clients with a proven methodology for navigating this process with aplomb, delivering a precise, high-efficiency process for building map-data pipelines of any scale with ease.

After selecting map data sources tailored to client-defined project goals, we can begin sourcing data, strategically utilizing private vendors and publicly available data sources. Once the map data has been curated and organized, full-scale analysis and annotation efforts can begin.


Maps Requirements Analysis
Maps Collection and Curation
Translation Transcription and Transliteration
ML Automated Labeling and Annotation
Human Annotation and Labelling with Quality Control
Converting and Automating Ongoing Maps Data Requirements
Maps Data Moderation


Our end-to-end map and locational data capabilities provide enterprise-quality data while fulfilling highly unique client-established parameters. All data collection is customized in response to the specific needs of each client. From scanning physical documents to field research and scanning, we’re ready to help intake map data at any scale, at any level of complexity.

Our annotation, analysis, and labeling process mines the desired insight from raw maps, with an end result of elite quality, densely integrated data capable of training machine learning models or providing a location-rich foundation for other enterprise applications.

Even fairly simple moderation needs—like ensuring that user-submitted locations and directions don’t run afoul of content policies—require a surprisingly robust data pipeline to efficiently support. Smart automation can dramatically streamline these moderation processes, with humans brought in for subtler judgment calls wherever necessary.



Successful AI Data Items Delivered


Successful AI & Data Projects


Expert Annotators


PII Compliant

Pan India, US & EU



Data Acceptance and Accuracy


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