System Methodology
An in-depth look into the architectural decisions, pipeline workflows, and intelligent algorithms powering AQILYTICS.
Platform Architecture
AQILYTICS relies on a modern, decoupled architecture designed to maintain high performance in visualizing geospatial data while simultaneously supporting heavy lifting on the AI inference backend.
Multi-modal AI Symphony
Our intelligent engine orchestrates two primary models symbiotically:
- Telemetric Inference (XGBoost): The backbone prediction engine processes historical air quality variables mapped against geo-spatial meteorological data to forecast trends over the next 48-72 hours. These structural predictions guarantee data-driven exactitude.
- Generative Synthesis (Gemini API): The raw inference outputs are piped into a tuned LLM workflow that unpacks complex biochemical thresholds and frames them in actionable, human-readable insights optimized for localized geographic anomalies.
Data Pipeline & Persistence
Subscriptions and global telemetry histories are routed asynchronously via our Node.js gateway and persisted optimally using a Neon PostgreSQL distributed database.
Our nightly cron jobs interface directly with the Resend messaging topology to securely dispatch personalized, dynamically-rendered PDFs detailing high-priority localized atmospheric shifts to registered observers.
For more programmatic details, consult the Source Repository.
AQILYTICS Core Systems