Current session
IP: checking… Country: checking… Browser: detecting… Device: detecting… Timezone: detecting… UA: detecting…
AI DEV CLOUD

Incubating Intelligence Experiences

AI Dev Cloud is a playground born from the passion for experimenting with intelligent systems, emerging technologies, and new ways of building digital experiences.

Delivery pace Biweekly prototyping reviews
Collaboration Cross-disciplinary teams + SMEs
Impact Production-readiness checkpoints

EarthquakesPH

PhilVolcans is a Philippine seismic observability platform that compiles high-frequency earthquake feeds, computes energy and slip metrics, and publishes a single dashboard for operators and the public. The backend ingests events from tables and databases, applies geospatial filters, and derives aggregates such as counts, energy, total seismic moment, and kinematic proxies. Datasets are paired with AI-generated weekly overviews, trench attributions, depth histograms, and interactive maps that show live events, coverage, and heat patterns.

The interface renders metrics via charts with moving averages, heat maps, pie diagrams, and histograms so viewers can spot anomalies or persistent trends; access controls and admin tooling surface usage stats while keeping sensitive operations secured behind authentication. Forecast maps, cross-section artifacts, and cached blobs refresh automatically with metadata for transparency, while daily statistics and moment release histories pull from SQL stores so offline analyses remain possible. A math-summary routine recomputes b-values, moment rates, energy proxies, and slip estimates, storing compressed JSON snapshots for fast reads and audits.

The responsive dashboard layers tiles, legends, and tooltips to keep the story consistent across devices, with messaging that clarifies coverage, data cadence, and fault-dimension assumptions plus status cues when blobs or feeds are missing. Containerized services, scheduled math/extraction jobs, and maintenance scripts automate schema snapshots and exports, and optional heat-map, trench, and 3D cross-section modules refresh on demand. Explore what we monitor at phquake.ai-dev.cloud.

Focus PhilVolcans unifies seismic feeds, aggregates, and AI-written summaries for the Philippines
Stack Azure Tables & Blobs · SQL aggregates · AI summaries · Containerized services

EarthquakesIT

This dashboard monitors Italian seismicity in near real time. The backend fetches epicenters from the SeismicPortal FDSN service, filters them to Italy, and renders a planimetric Folium map with regional boundaries plus a 3D depth profile relative to key volcanoes. Operational Review lists the latest hour’s quakes in pill cards, while Insights generates a weekly overview via OpenAI every 12 hours and publishes magnitude/slip summaries from the past 30 days—everything cached server-side with JSON endpoints for reuse. Helpers fetch elevation grids, highlight Italian regions, and annotate the five most relevant volcanoes, all wrapped in a clean bilingual UI. Explore the live dashboard at itaquakes.ai-dev.cloud.

Focus Translating civic tech UX patterns to European datasets
Stack Flask · Python · Azure Functions · Storage Tables

Crypto Trends Analysis

Functional prototype that orchestrates Microsoft Azure services to automate crypto-portfolio intelligence. It uses a low-cost, serverless pipeline to collect heterogeneous signals, normalize them, and expose the data for downstream analytics—such as an AI-driven advisory engine. Azure Functions (Python) query external feeds, transform payloads, and persist results to Azure Storage Tables, all built and managed via Visual Studio Code with Azure tooling.

Explore the live Crypto Trends Analysis surface at crypto.ai-dev.cloud.

Focus Spotting early momentum through qualitative + quantitative signals
Stack Python · Flask · Azure Functions · SQL Server · OpenAI APIs

Exploration

Hands-on prototyping across AI, UX, and infrastructure

Community

Open sharing of lessons, references, and playbooks

Craft

Design-first approach to every experiment

Momentum

Continuous iteration with curiosity-led roadmaps