# Elevation API Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/elevation-api
> Markdown URL: https://aitinkerers.org/technologies/elevation-api.md
> Technology record last updated: 2026-10-02T09:38:58Z
> Generated: 2026-10-14T07:03:22Z

Get precise elevation data for any global location: fast, accurate, and direct.

The Elevation API provides elevation data for all landmasses and ocean floor locations worldwide, offering a simple interface to query locations. Input single points or multiple ordered points along a path (up to 512 per request) and receive highly accurate altitude measurements. This tool is critical for applications requiring precise vertical positioning, such as mapping, surveying, and environmental analysis, integrating seamlessly into existing geospatial workflows.

- Official technology site: https://developers.google.com/maps/documentation/elevation
- Public AI Tinkerers demos and talks: 1
- Result page: 1 of 1

## Recent Public Talks and Demos

### [NextSpot: Travel-proof recommendations powered by Google Maps reviews understanding (not keyword search)](https://atlanta.aitinkerers.org/talks/rsvp_Lr0MUd5Hy_4)

NextSpot is a live web demo that recommends similar places in a new city by understanding what your favorite spot is known for from public signals (reviews + description). In the demo, I’ll enter a favorite place and a target location (e.g., Dallas/Houston). NextSpot extracts the place’s “signature attributes,” generates a compact intent query, searches locally within a strict radius, and returns recommendations constrained to the same business category (e.g., cafe → cafe, salon → salon). The result is a recommender that works across many categories without hardcoding for any single domain. In 5 minutes, I’ll show the working web app and a short walkthrough of the backend internals: 1) pulling place metadata + top reviews, 2) extracting “signature attributes” into structured fields (not freeform text) 3) turning those fields into a constrained search query, 4) retrieving candidates from Places within a hard geo-radius, then 5) ranking results with embeddings + a lightweight re-ranker

- Event context: Co-Co-Code & Cocoa: The AI Tinkerers Atlanta Holiday Meetup — 2025-12-16 — Atlanta
- Public talk page: https://atlanta.aitinkerers.org/talks/rsvp_Lr0MUd5Hy_4

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