03 / Enterprise IT & Applied AI
Industrial intelligence
for a complex world.
We engineer enterprise software and applied AI systems for industrial operations — predictive maintenance, combustion optimization, and offline-first field platforms operating at 99.98% uptime across 60+ production systems globally.
60+
Production Systems
Active nodes
99.98%
Uptime SLA
Mission-critical
72hr
Failure Prediction
Advance warning
02. Specialized Engineering Capabilities
Four production-grade systems.
72hr
Predictive failure lead time
Predictive Maintenance & Anomaly Detection
Custom machine learning models analyzing vibration, temperature, and acoustic sensor streams to predict industrial equipment failure up to 72 hours in advance — before downtime occurs.
- PyTorch sensor fusion models
- Vibration & acoustic FFT analysis
- 72-hour failure prediction window
- Integration with CMMS systems
9.2%
Average monthly fuel reduction
Industrial Combustion Optimization
Reinforcement learning algorithms continuously adjusting fuel-to-air ratios and damper positions on utility-scale boilers to maximize thermal efficiency — reducing natural gas consumption without equipment replacement.
- RL combustion control loops
- Flue gas sensor integration (O₂, CO, stack temp)
- Dynamic damper automation
- Real-time thermal efficiency monitoring
Zero
Connectivity required for field audits
Offline-First Mobile Audit Suites
Cross-platform mobile applications equipped with camera OCR and edge processing, enabling field engineers to log physical audits in zero-connectivity environments with instant cloud synchronization when connection is restored.
- React Native with offline-first architecture
- Camera OCR for document digitization
- Edge processing for zero-connectivity operation
- End-to-end encrypted cloud sync
60+
Active production nodes
Industrial IoT Telemetry Hubs
End-to-end telemetry pipelines from field sensor calibration to cloud time-series storage — ingesting data from industrial Modbus RTU/TCP devices, SCADA systems, and smart energy meters.
- MQTT & Modbus protocol integration
- Apache Kafka for high-throughput ingestion
- TimescaleDB for time-series storage
- Real-time alerting and anomaly detection
03. Production Technology Stack
Battle-tested at industrial scale.
Every technology in our stack is selected for production reliability, not developer preference. We operate in environments where failure means unplanned downtime and real financial loss.
Architecture Layer
Production Technologies
Purpose
Edge & Ingestion
Rust, Python, MQTT, Apache Kafka, Modbus
Industrial sensor acquisition and edge processing
Data Persistence
TimescaleDB, PostgreSQL, Redis, AWS S3
High-frequency time-series and relational records
AI & Machine Learning
PyTorch, XGBoost, Scikit-learn, MLflow
Combustion tuning and predictive anomaly models
DevOps & Cloud
Docker, Kubernetes, Terraform, AWS, GCP
Zero-downtime microservices and cloud governance
04. SLA Commitments
Contractually committed uptime.
Our enterprise contracts include contractual uptime SLAs, incident response guarantees, and data retention commitments — backed by our infrastructure team and cloud redundancy architecture.
Submit an RFP
Request a systems consultation.
Tell us your scope — IoT, ML, enterprise web, or offline mobile — along with your timeline, budget tier, and target infrastructure. We respond within 5 business days.
- <$100KProof-of-concept & pilots
- $100K – $250KProduction system deployment
- $250K+Full enterprise integration