# Azure Functions Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/azure-functions
> Markdown URL: https://aitinkerers.org/technologies/azure-functions.md
> Technology record last updated: 2026-04-01T17:02:55Z
> Generated: 2026-09-22T02:45:04Z

Azure Functions is an event-driven serverless compute platform that scales automatically to handle everything from HTTP requests to complex background data processing.

Azure Functions eliminates infrastructure management by executing code only when specific triggers occur: think HTTP webhooks, timer-based cleanups, or new messages in an Azure Service Bus queue. You write logic in languages like C#, Python, or JavaScript, while the platform handles the scaling from zero to thousands of concurrent instances. With the Consumption plan, you only pay for the exact execution time and memory used (the first 1 million requests per month are free). It integrates natively with the broader Azure ecosystem through bindings, allowing you to read from Cosmos DB or write to Blob Storage with minimal boilerplate code.

- Official technology site: https://learn.microsoft.com/en-us/azure/azure-functions/
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [CTRL+F for your stuff : Building a scalable, resilient and secure multi-modal vision search solution](https://raleigh.aitinkerers.org/talks/rsvp_S9zghJZIZWE)

WhichBox is a web app that lets you photograph your storage boxes and uses Vision AI to build a searchable inventory, so you can ask "where is my phone charger?" and get a ranked, confidence-scored answer. In this demo, I'll walk through three technical problems I had to solve while building this solution.

- Event context: AI Tinkerers Raleigh Meetup — May 6, 2026 — 2026-05-06 — Raleigh
- Public talk page: https://raleigh.aitinkerers.org/talks/rsvp_S9zghJZIZWE

### [RAG Copilot: Big Data-powered solutions for rapid Information extraction](https://medellin.aitinkerers.org/talks/rsvp_1rdidJ3owc8)

Solution for Automatic Content Extraction from Large Data Volumes Using a RAG (Retrieval Augmented Generation) Model and AWS Serverless Architecture with a MapReduce Approach

- Event context: Lanzamiento de AI Tinkerers #1 — 2024-04-25 — Medellín
- Public talk page: https://medellin.aitinkerers.org/talks/rsvp_1rdidJ3owc8

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