# Overview **HASTE** (High-speed Assessment and Satellite Tracking for Emergencies) is an AI-powered tool from the **Microsoft AI for Good Lab** for quickly assessing building damage after a disaster. You add satellite imagery, label a small amount of it, and HASTE predicts damage across the whole area. ## Choose your path HASTE offers two workflows that both turn imagery into a damage assessment — pick based on what you need and how fast you need it. | | {doc}`Rapid Building Assessment ` | {doc}`Damage Mapping ` | |---|---|---| | **How it works** | Embed buildings → label a few → an in-browser model predicts the rest → validate → report | Draw labels → train a segmentation model → predict across the whole image | | **Output** | Per-building damaged/intact, with accuracy metrics and a damaged-building estimate | A continuous damage map + downloadable geopackage | | **Speed** | Minutes — no training job | Slower — GPU model training and inference | | **Needs** | Building footprints for the area | Just imagery | ```{admonition} Not sure? Start here. :class: tip If you have building footprints and want an answer fast, use {doc}`Rapid Building Assessment ` — it's the quickest route from imagery to a damage assessment. Choose {doc}`Damage Mapping ` when you need a continuous, pixel-level damage raster. ``` Both workflows start the same way — create a project and add an image layer — then diverge. Those shared building blocks have their own pages: {doc}`Projects `, {doc}`Image layers `, and the {doc}`Model catalog `.