# Geolantis: High Precision Data Collection

> Geolantis\.360 turns mobile devices into high\-precision GNSS tools for fast, accurate underground utility mapping with GIS/CAD integration and real\-time cloud sync\.

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## Pages
- [Home](https://geolantis.com/)
- [](https://geolantis.com/geolantisneo/)
- [Geolantis\.360 \+ GLRM Expert Bundle](https://geolantis.com/geolantis-360-glrm-expert-bundle/)
- [GIS Mapping Tool](https://geolantis.com/geospatial-mapping-solutions/gis-mapping-tool/)
- [Utility Mapping Playbook](https://geolantis.com/utility-mapping-playbook/)

## Posts
- [How to Map Utilities at Scale and Manage Large Projects Without Losing Control](https://geolantis.com/news/how-to-map-utilities-at-scale-and-manage-large-projects-without-losing-control/): Scaling a utility mapping program does not automatically create a data quality problem, but it does create the conditions for one\. When a single crew operates in a defined area with a clear scope, data consistency is manageable through direct oversight and routine checking\. Add three more crews, spread them across multiple sites and introduce a range of asset types, and the same oversight mechanisms stop working\. The problem is structural, not operational\. Coordination tools, additional headcount and more frequent check\-ins do not fix it\. Three failure points drive the breakdown at scale: inconsistent data capture, uncontrolled permissions and a broken handoff between field and office\. 
- [From Field to Office: How Teams Can Collaborate Around a Single Source of Truth](https://geolantis.com/news/from-field-to-office-how-teams-can-collaborate-around-a-single-source-of-truth/): Field\-to\-office data lag is not a structural problem, built into workflows that were designed for single\-user data entry rather than multi\-team, multi\-location projects\. When field crews capture data to a local file, transfer it to a shared drive or email it to the office at the end of the day, and GIS teams import and reformat it before a project manager can generate a report, every step in that sequence produces a version of the dataset that is already behind the current state of the field\. Three symptoms follow reliably: version conflicts between datasets submitted by different crews, duplicate data entry as office teams manually re\-enter or reformat field records, and decisions made on information that no longer reflects what is happening on site\. 
- [How to Prepare Telecom Network Data for Future Maintenance and Regulatory Compliance](https://geolantis.com/news/how-to-prepare-telecom-network-data-for-future-maintenance-and-regulatory-compliance/): Telecom infrastructure data collected without a structured workflow does not simply age;  it degrades in usefulness\. Records that omit burial depth, carry no installation date or use inconsistent attribute coding across contractors cannot reliably support a maintenance decision, a dig permit application or a regulatory audit\. The gap between what was installed and what is documented grows over time, not because records are lost, but because they were never captured with sufficient structure to serve the use cases that follow installation\. Compliance\-ready data is not produced at the reporting stage\. It is produced during field collection, or it requires expensive and often incomplete remediation to produce later\.
- [What Happens Between Field Collection and GIS Import and How to Avoid Data Loss](https://geolantis.com/news/what-happens-between-field-collection-and-gis-import-and-how-to-avoid-data-loss/): Data loss in utility mapping projects rarely happens on site\. It happens in the steps that follow the site visit:  the file export, the email attachment, the format conversion, the manual import,  each one a point where data degrades silently and without warning\. Most project managers treat field work as the high\-risk phase and assume that once the crew returns, the hard part is done\. The evidence says otherwise\. This article maps the traditional field\-to\-GIS handover chain, names the failure modes at each step and covers what it takes to close the gaps\.
- [How to Achieve Accurate Utility Mapping in the Field](https://geolantis.com/news/how-to-achieve-accurate-utility-mapping-in-the-field/): Accurate utility mapping does not begin with the device in a field technician's hand; it begins with the workflow that governs how that technician captures, classifies and submits data\. Most mapping errors that surface during design reviews, asset audits or excavation planning trace back to a process gap, not a sensor failure\. This article covers the field practices, validation routines and software design principles that separate reliable utility data from data that requires expensive rework\.

## UX Blocks
- [Footer 2](https://geolantis.com/news/blocks/footer-2/)
- [Request Demo Form](https://geolantis.com/news/blocks/request-demo-form/)
- [Contact Form](https://geolantis.com/news/blocks/contact-form/)
- [Footer](https://geolantis.com/news/blocks/footer/)

## Optional
- [Sitemap index](https://geolantis.com/sitemap_index.xml)