Foresight Spatial Labs provides a cloud‑native, collaborative CAD platform and a high‑performance spatial database called SpatialDrive for handling time‑series 3D data. Built with Rust and Bevy, the system streams billions of points with attribute‑rich volumetric storage, supports GPU‑accelerated meshless physics, and enables real‑time multi‑user editing across desktop, mobile, web, and server environments.
Funding
Funding not disclosed
Founders
Product
Problem
Professionals handling large-scale spatial datasets face bottlenecks in storing, visualizing, and collaborating on time‑varying 3D data. Existing CAD and GIS tools often require heavyweight workstations, lack efficient streaming of billions of points, and do not treat temporal changes as a first‑class element, limiting real‑time perception and joint editing.
Solution
Foresight Spatial Labs offers cloud‑native, collaborative CAD and a specialized database called SpatialDrive that is built for time‑series 3D data. By combining temporal indexing with a high‑performance renderer, SpatialDrive streams only the requested geometry and attributes, enabling instant query changes and visualization of billions of points on consumer hardware. The platform supports arbitrary attribute enrichment of 3D volumes, GPU‑accelerated physics simulations, and both implicit and discrete constructive solid geometry operations. Collaboration is facilitated through versioned, cloud‑based data storage where time is treated as a first‑class dimension, allowing multiple users to edit and view up‑to‑date spatial models simultaneously.
Target Audience
Primary customers are engineering teams in robotics, mining, simulation, and construction that require high‑performance, collaborative handling of large, time‑varying 3D datasets, as well as software vendors seeking a white‑label spatial data engine.
Features
- Source‑available SDK built with Rust and Bevy, deployable on desktop, mobile, web, and server environments
- Temporal indexing and streaming renderer that delivers sub‑second visualization of billions of points with selective attribute loading
- Attribute‑rich volumetric storage enabling custom data (e.g., classifications, ore grades, strain metrics) to be attached to 3D space
- GPU‑accelerated meshless multiphysics simulations runnable locally or on cloud servers
- Implicit and discrete CSG tools for cutting, merging, and manipulating point clouds, block models, meshes, and mathematical representations
- Cloud‑native collaborative CAD with versioned data and real‑time multi‑user editing