GeoScope

GeoScope uses sandboxed AI agents on Vultr to design local facilities, check land fit, and compare walking access before and after.

Live demoGitHub0

Overview

GeoScope helps planners and community teams explore where a clinic, library, school or community centre could fit and whether it would improve access. Users select a neighborhood and set building and open-space goals. An agent plans the analysis, generates Python, and tests layouts against supplied parcels, buildings and roads. Results show checked alternatives, existing nearby facilities, a 3D preview, and estimated walking access before and after the proposal. Vultr Compute Instances host the FastAPI controller and a separate worker connected through a private VPC. All agent LLM calls use Vultr Serverless Inference. Generated code executes inside disposable gVisor containers with no outbound network, read-only inputs and resource limits. A fresh sandbox recomputes submitted designs before displaying results, with downloadable code, metrics and execution traces. The demos cover San Francisco and East Harlem. SF candidate plots are simulated; geometric checks do not establish land ownership or construction approval.

Note: the demo URL is substituted with the GitHub repository link.

Tech stack

No comments yet

Be the first to comment on this project.