Teleport API
Jul 16,2026

GISBox is a one-stop 3D GIS data editing, conversion and publishing platform that supports editing in multiple GIS formats such as OSGB/GEOTIFF/RVT, converting to 3DTiles/Terrain and publishing.

Introduction

Teleport API is a cloud-based interface service built on 3D Gaussian Splatting technology for spatial data processing scenarios. It supports uploading image and video capture data to automatically generate real-world 3D reconstruction models. These 3D assets, ranging from lightweight models to highly photorealistic reconstructions, can be seamlessly integrated into a developer’s own workflows, visualization platforms, or VR/AR applications. With the help of elastic GPU clusters, Teleport API also supports automated batch processing and can handle spatial datasets ranging from a single scene to city-block-scale environments.

File Structure

The file structure of Teleport API for spatial data processing and analysis can be divided into the following core parts:

Project root directory: Contains the main configuration and build-related files, such as teleport.yaml for primary service configuration, go.mod and go.sum for dependency management, LICENSE for the open-source license, and Makefile for build rules. These files define global service parameters, dependency versions, and build behavior.
api/ core interface directory: Stores the main API-related code, typically divided into modules such as auth for authentication, events for event handling, services for business logic, and utils for shared utilities. These support core interfaces such as spatial data upload, 3D reconstruction, and result export.
cmd/ command-line tools directory: Contains three main entry points: the teleport daemon startup file, the tctl cluster management tool, and the tsh user cluster access tool. These are used for deployment, operations, and user access workflows.
docs/ documentation directory: Covers administrator guides, architecture descriptions, getting-started tutorials, and user manuals, providing deployment instructions and API usage references for the spatial data processing service.
examples/ scenario examples directory: Includes integration examples for environments such as Kubernetes, PostgreSQL, and SSH, helping developers quickly connect to the spatial data processing capabilities.
web/ frontend resources directory: Stores code for the web-based visualization interface, including app application logic, assets static resources, components component libraries, and styles style files, supporting online preview of 3D reconstruction results.
scripts/ operations scripts directory: Contains automation scripts for building, documentation generation, and testing, used to support operations for large-scale spatial data processing tasks.

Pros

High-fidelity, large-scale processing capability: Powered by 3D Gaussian Splatting, it can balance cost and visual quality from lightweight models to highly photorealistic reconstructions, and it supports very large scenes such as city-block environments with over 100 million splats.
End-to-end workflow automation: It can integrate directly into existing content production workflows, support direct export of processed 3D models, or embed its built-in renderer into external products, significantly reducing manual effort in spatial data processing.
Enterprise-grade service support: Backed by elastic GPU clusters, it can support large numbers of batch reconstruction tasks per day, while also providing data ownership controls, privacy protection, and enterprise-level security features for large-scale commercial use.
Low integration barrier: Developers can quickly integrate advanced 3D reconstruction capabilities through standardized APIs without building the underlying compute and algorithm stack from scratch.

Cons

Limited scenario coverage: Its main strength is real-world 3D reconstruction, but it is less suitable for broader GIS use cases such as vector spatial analysis or large-scale spatiotemporal statistics.
Higher usage cost: Highly photorealistic reconstruction for large scenes requires substantial GPU resources, which can make service usage relatively expensive for small and medium-sized developers, especially at high frequency and scale.
Ecosystem compatibility gaps: As a specialized vertical service, its compatibility with general GIS platforms and traditional spatial-data processing toolchains still has room for improvement, and preprocessing older spatial data formats may require extra effort.
Strong network dependency: Core 3D reconstruction computation is performed entirely in the cloud, so the service cannot be used offline, which makes it less suitable for field data-collection scenarios with unstable connectivity.

Application Scenario

Teleport API uses cloud-based 3D reconstruction capabilities to automatically convert captured image and video data into high-fidelity real-world 3D models. It is widely used in areas such as digital twin city construction, offline space digitization and archival, immersive cultural and tourism content production, and real-world reconstruction for architecture and construction. Developers can also embed it into their own products to quickly enable real-time spatial-data visualization and lightweight interaction, supporting digitalization needs from a single room to entire urban blocks.