# Workflows Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/workflows
> Markdown URL: https://aitinkerers.org/technologies/workflows.md
> Technology record last updated: 2026-03-16T18:16:32Z
> Generated: 2026-09-20T23:53:58Z

Workflows automate and orchestrate complex, multi-step processes: chaining microservices, APIs, and functions into a single, reliable application.

Workflows are the engine for coordinating distributed systems, defining a structured series of steps (states) to execute tasks reliably. They manage the sequence, logic (if/then), and state of a process, ensuring steps complete in the correct order. Key platforms like AWS Step Functions and Google Cloud Workflows use a visual state machine model to build these flows. This technology is critical for use cases such as ETL pipelines (Extract, Transform, Load), automating invoice approval processes, or building 'human-in-the-loop' systems that wait for external input for up to one year. Workflows automatically handle error retries and fault tolerance, significantly reducing the boilerplate code required to manage application complexity and dependencies across dozens of services.

- Official technology site: https://cloud.google.com/workflows
- Public AI Tinkerers demos and talks: 2
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Can AI Hear a Crisis? Building a Real-Time 911 Audio Classification Pipeline on Azure](https://doha.aitinkerers.org/talks/rsvp_TSXbqExBe48)

We built an end-to-end cloud-native AI system on Azure that classifies 911 emergency calls into medical, fire, or violence categories using the first 30 seconds of audio. The project combines audio feature engineering, MLOps workflows, and automated retraining pipelines to support dispatcher decision-making with probabilistic confidence scores. During the demo, I’ll walk through the full architecture: Azure Data Lake Medallion design, Databricks ETL pipeline, Voice Activity Detection preprocessing, MFCC feature extraction, Azure ML training pipelines, GitHub-triggered CI/CD workflows, automated retraining, model registration, and the live deployed endpoint workflow.

- Event context: AI Tinkerers – Doha Inaugural Meetup — 2026-05-18 — Doha
- Public talk page: https://doha.aitinkerers.org/talks/rsvp_TSXbqExBe48

### [Building a Sign Language Translator in 5 Minutes](https://sf.aitinkerers.org/talks/rsvp_13YKmPbjwy8)

I'll be building an American Sign Language (ASL) translator using Computer Vision in less than 5 minutes using Roboflow. To do this, I'll be leveraging Roboflow Edge, which allows users to set up an NVIDIA Jetson from scratch using one command. After setting up the Jetson, I'll then modify the logic running on the device using Workflows, a new no-code tool that Roboflow has been building. Once I've modified the logic running on the device, I'll lastly connect the Jetson to a speaker and it will start speaking the sign language gestures that I'm making out loud.

- Event context: AI Tinkerers - San Francisco - Summer Edition - July 2024 — 2024-07-12 — San Francisco
- Public talk page: https://sf.aitinkerers.org/talks/rsvp_13YKmPbjwy8

## Related Technologies

- [Azure Databricks](https://aitinkerers.org/technologies/azure-databricks) ([Markdown](https://aitinkerers.org/technologies/azure-databricks.md)) — 1 public demo
- [Azure Data Lake Gen2](https://aitinkerers.org/technologies/azure-data-lake-gen2) ([Markdown](https://aitinkerers.org/technologies/azure-data-lake-gen2.md)) — 1 public demo
- [Azure DevOps](https://aitinkerers.org/technologies/azure-devops) ([Markdown](https://aitinkerers.org/technologies/azure-devops.md)) — 1 public demo
- [Azure Machine Learning](https://aitinkerers.org/technologies/azure-machine-learning) ([Markdown](https://aitinkerers.org/technologies/azure-machine-learning.md)) — 1 public demo
- [Computer Vision](https://aitinkerers.org/technologies/computer-vision) ([Markdown](https://aitinkerers.org/technologies/computer-vision.md)) — 22 public demos
- [Data](https://aitinkerers.org/technologies/data) ([Markdown](https://aitinkerers.org/technologies/data.md)) — 8 public demos
- [ETL](https://aitinkerers.org/technologies/etl) ([Markdown](https://aitinkerers.org/technologies/etl.md)) — 3 public demos
- [Librosa](https://aitinkerers.org/technologies/librosa) ([Markdown](https://aitinkerers.org/technologies/librosa.md)) — 2 public demos
- [Model Training](https://aitinkerers.org/technologies/model-training) ([Markdown](https://aitinkerers.org/technologies/model-training.md)) — 2 public demos
- [NVIDIA Jetson](https://aitinkerers.org/technologies/nvidia-jetson) ([Markdown](https://aitinkerers.org/technologies/nvidia-jetson.md)) — 3 public demos
- [pipeline orchestration](https://aitinkerers.org/technologies/pipeline-orchestration) ([Markdown](https://aitinkerers.org/technologies/pipeline-orchestration.md)) — 1 public demo
- [Roboflow](https://aitinkerers.org/technologies/roboflow) ([Markdown](https://aitinkerers.org/technologies/roboflow.md)) — 1 public demo
- [Roboflow Edge](https://aitinkerers.org/technologies/roboflow-edge) ([Markdown](https://aitinkerers.org/technologies/roboflow-edge.md)) — 1 public demo