# Cloud Projects at AI Tinkerers

> Canonical HTML: https://aitinkerers.org/technologies/cloud
> Markdown URL: https://aitinkerers.org/technologies/cloud.md
> Technology record last updated: 2026-02-25T05:30:34Z
> Generated: 2026-09-22T04:37:46Z

A high-performance hybrid workflow that offloads heavy blockchain interoperability tasks to local Apple Silicon while maintaining a cloud-native Node.js presence on Replit.

This architecture leverages the M3 Max's 400GB/s memory bandwidth to run resource-intensive Hyperledger Cacti connectors and Dockerized ledgers locally, bypassing Replit's standard container limits. By establishing a secure edge-cloud bridge via Tailscale or a specialized WebSocket tunnel, the Node.js application on Replit handles the logic and global accessibility while the local hardware manages the heavy lifting. This setup reduces transaction simulation latency to sub-10ms and provides a 5x performance boost over pure cloud environments for complex cross-chain development.

- Official technology site: https://github.com/hyperledger-cacti/cacti
- Public AI Tinkerers demos and talks: 4
- Result page: 1 of 1

## Recent Public Talks and Demos

### [Building an ML Decision Lab for Agriculture: Turning Predictions into Learning](https://lausanne.aitinkerers.org/talks/rsvp_4vwa4V9v2ek)

FarmBuddy is an interactive machine learning decision-support system built with Streamlit and a Random Forest regression pipeline. Users can modify agricultural inputs such as crop type, fertilizer usage, land area, and season, then observe how model predictions change in real time. Beyond prediction, the system includes decision logging, before-and-after scenario comparison, input validation, and a learning summary layer designed to help users understand how machine learning models respond to changing conditions. During the demo, I will show the live application, model inference workflow, session-state architecture, and the decision comparison engine.

- Event context: AI Tinkerers Lausanne June 2026 Meetup — 2026-06-25 — Lausanne
- Public talk page: https://lausanne.aitinkerers.org/talks/rsvp_4vwa4V9v2ek

### [Engenheiro civil + Claude Code: app de terraplenagem 100% determinístico construído por conversa](https://curitiba.aitinkerers.org/talks/rsvp_iwCDvtHEc-s)

KML Earthworks é um app Streamlit que transforma um traçado de estrada de acesso desenhado no Google Earth em estimativa de terraplenagem (perfil longitudinal, volumes de corte/aterro pela fórmula do prismatoide, balanço de massa, diagrama de Bruckner) em segundos — upload de .kml, download de Excel, zero GIS de desktop. Na demo eu vou: (1) desenhar um acesso ao vivo no Google Earth e rodar o app em produção (kml-earthworks.streamlit.app) mostrando o pipeline completo (parse → stationing a cada 20m → enriquecimento de elevação com fallback de API → otimização de grade → volumes → export); (2) abrir o repo no editor e mostrar a estrutura src/ modular, o CLAUDE.md que funciona como guideline persistente para o agente, e rodar os 58 testes ao vivo no terminal; (3) navegar pelos commits para mostrar a evolução notebook → pacote → app por desenvolvimento conversacional com Claude Code, incluindo os pontos onde eu tive que intervir manualmente.

- Event context: AI Tinkerers Curitiba: Evento Inaugural — 2026-06-10 — Curitiba
- Public talk page: https://curitiba.aitinkerers.org/talks/rsvp_iwCDvtHEc-s

### [Routing to the right LLMs, dynamically than hard coding. Catching Cost issues in the code](https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_-KpxPGzcak8)

I will present 2 developer centrics solutions - 1. CloudVerse AIX - dynamically routing to the correct LLMs under cost, latency, qualty and compliance constraints, than hardcoding LLMs. This solution tracks over 600 Models globally and can route to any under controlled directions. 2. CloudVerse DevX - DevFinOps AI bot. The bot sits inside repos, CLIs and AI agents, identified cost issues in code at the time of commit or PRs. The prevents costly issues from entering into production.

- Event context: AI Tinkerers Ho Chi Minh City: From Prompt to Agent — 2026-03-07 — Ho Chi Minh City
- Public talk page: https://ho-chi-minh-city.aitinkerers.org/talks/rsvp_-KpxPGzcak8

### [Tricks for building + hosting personal AI systems](https://san-diego.aitinkerers.org/talks/rsvp_i-fmBqL4sFo)

Best practices I've learned for building and hosting your own personal AI agents

- Event context: AI Tinkerers x Google AI Meetup, San Diego — 2025-11-21 — San Diego
- Public talk page: https://san-diego.aitinkerers.org/talks/rsvp_i-fmBqL4sFo

## Related Technologies

- [NumPy](https://aitinkerers.org/technologies/numpy) ([Markdown](https://aitinkerers.org/technologies/numpy.md)) — 6 public demos
- [Pandas](https://aitinkerers.org/technologies/pandas) ([Markdown](https://aitinkerers.org/technologies/pandas.md)) — 10 public demos
- [Streamlit](https://aitinkerers.org/technologies/streamlit) ([Markdown](https://aitinkerers.org/technologies/streamlit.md)) — 89 public demos
- [Amazon Bedrock](https://aitinkerers.org/technologies/amazon-bedrock) ([Markdown](https://aitinkerers.org/technologies/amazon-bedrock.md)) — 20 public demos
- [Claude Code](https://aitinkerers.org/technologies/claude-code) ([Markdown](https://aitinkerers.org/technologies/claude-code.md)) — 215 public demos
- [com cooldown mecânico no cliente xml](https://aitinkerers.org/technologies/com-cooldown-mec-nico-no-cliente-xml) ([Markdown](https://aitinkerers.org/technologies/com-cooldown-mec-nico-no-cliente-xml.md)) — 1 public demo
- [Cost Optimization](https://aitinkerers.org/technologies/cost-optimization) ([Markdown](https://aitinkerers.org/technologies/cost-optimization.md)) — 1 public demo
- [Cursor](https://aitinkerers.org/technologies/cursor) ([Markdown](https://aitinkerers.org/technologies/cursor.md)) — 65 public demos
- [DevOps](https://aitinkerers.org/technologies/devops) ([Markdown](https://aitinkerers.org/technologies/devops.md)) — 3 public demos
- [joblib](https://aitinkerers.org/technologies/joblib) ([Markdown](https://aitinkerers.org/technologies/joblib.md)) — 1 public demo
- [LLM](https://aitinkerers.org/technologies/llm) ([Markdown](https://aitinkerers.org/technologies/llm.md)) — 123 public demos
- [Matplotlib](https://aitinkerers.org/technologies/matplotlib) ([Markdown](https://aitinkerers.org/technologies/matplotlib.md)) — 2 public demos
- [Open-Meteo Elevation API](https://aitinkerers.org/technologies/open-meteo-elevation-api) ([Markdown](https://aitinkerers.org/technologies/open-meteo-elevation-api.md)) — 1 public demo
- [Plotly](https://aitinkerers.org/technologies/plotly) ([Markdown](https://aitinkerers.org/technologies/plotly.md)) — 7 public demos
- [Python](https://aitinkerers.org/technologies/python) ([Markdown](https://aitinkerers.org/technologies/python.md)) — 662 public demos
- [Random Forest regression](https://aitinkerers.org/technologies/random-forest-regression) ([Markdown](https://aitinkerers.org/technologies/random-forest-regression.md)) — 1 public demo
- [scikit-learn](https://aitinkerers.org/technologies/scikit-learn) ([Markdown](https://aitinkerers.org/technologies/scikit-learn.md)) — 84 public demos
- [Scikit-learn Random Forest pipeline](https://aitinkerers.org/technologies/scikit-learn-random-forest-pipeline) ([Markdown](https://aitinkerers.org/technologies/scikit-learn-random-forest-pipeline.md)) — 1 public demo