AI-Powered Infrastructure

A multi-cloud, specialized stack designed for industrial IoT, low-latency streaming, and high-performance AI inference.

AI Technology & Data Engine

Our AI continuously processes real-time telemetry from thousands of building sensors to optimize energy and predict failures.

Data Ingested

Real-time BACnet/Modbus telemetry streams from thousands of connected building sensors.

  • Compressor power draw & refrigerant pressure
  • Duct velocity & room micro-occupancy sensors
  • Weather API feeds & spot energy pricing
  • Vibration spectral data from motor sensors
  • Ambient temperature & humidity readings

AI Outputs

Actionable intelligence delivered in real time to facility managers and autonomous control systems.

  • Real-time airflow adjustment commands
  • 14-day anomaly score predictions for mechanical failure
  • Automated carbon reduction reports
  • Dynamic setpoint overrides vs baseline schedules
  • Predictive maintenance scheduling

Models & Techniques

Deep Learning

Multi-Variable Time-Series Transformers

Attention-based neural networks that process concurrent multi-sensor time series data to detect complex patterns in HVAC system behavior.

Reinforcement Learning

Dynamic Setpoint RL Agents

Self-learning agents that continuously discover optimal temperature setpoints by balancing energy cost, occupant comfort, and equipment longevity.

Signal Processing

FFT Vibration Spectral Analysis

Frequency-domain analysis of motor vibration signatures to identify bearing wear, rotor imbalance, and mechanical degradation patterns.

Technology & Infrastructure Stack

A multi-cloud architecture purpose-built for industrial IoT, real-time streaming, and AI inference at scale.

IoT Ingestion & Protocol Layer

EMQX Enterprise / Eclipse Mosquitto

High-performance distributed MQTT brokers handling thousands of message payloads per second from edge gateways.

EdgeX Foundry

Open-source edge computing framework deployed on local gateways for BACnet, Modbus, and OPC UA protocol translation.

Data Engineering & Streaming Pipeline

Apache Kafka & Flink

Distributed event streaming and real-time stateful stream processing for immediate sensor anomaly detection.

TimescaleDB / InfluxDB

Specialized time-series databases optimized for fast ingestion and rapid querying of multi-year sensor telemetry.

Redis Enterprise

Ultra-low latency in-memory data store for caching real-time building thermal states and active setpoint overrides.

AI Model Training & Deployment

NVIDIA CUDA, TensorRT, Triton

GPU acceleration for fast spectral analysis, model optimization, and Triton Inference Server for managing concurrent AI models.

PyTorch & Ray

PyTorch for deep learning time-series transformers; Ray for distributed reinforcement learning training at scale.

Cloud, Compute & Orchestration

AWS (S3, ECS, Lambda, Bedrock)

S3 for long-term telemetry archive, ECS/Lambda for microservice orchestration, Bedrock for natural language query tools.

Docker & Kubernetes

Containerized microservices with auto-scaling based on incoming telemetry volume across multi-cloud workloads.

Edge Delivery

Cloudflare / Vercel

High-speed edge network for delivering the frontend dashboard with sub-second response times globally.

How We Use Cloud & GPU

How We Use AWS

  • Amazon S3: Long-term raw telemetry archive with lifecycle policies
  • Amazon ECS & Lambda: Microservice orchestration for streaming and inference pipelines
  • Amazon Bedrock: Natural language query interface (Exertia Bot) for facility managers
  • Amazon RDS: Relational database for user accounts, billing, and configuration

How We Use NVIDIA

  • CUDA: GPU-accelerated FFT for vibration spectral analysis on streaming data
  • TensorRT: Model optimization for low-latency inference at the edge and in cloud
  • Triton Inference Server: Managing concurrent AI models with auto-scaling
  • NVIDIA Jetson: Future edge AI deployment for on-premise gateway inference

How It Works

From sensor data to autonomous HVAC optimization in four steps.

01

Connect

Install edge gateways that translate BACnet, Modbus, and OPC UA protocols into a unified telemetry stream via MQTT.

02

Ingest

Sensor data flows through Kafka and Flink pipelines into TimescaleDB, with Redis caching real-time thermal states.

03

Analyze

AI models process the data in real time: transformers detect anomalies, RL agents optimize setpoints, FFT analyzes vibration.

04

Optimize

Autonomous setpoint adjustments are pushed to the BMS. Predictive alerts notify facility managers 14 days before failure.