Deployment options
Orpheon is prepared for managed cloud, private VPC, and on-prem setups, including edge-to-cloud data flow and container-native delivery.
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Pre-configured templates and proven pipelines for finance, energy, and oil & gas — each with measurable ROI and domain-specific optimizations.



Live interactive canvas — explore pre-built industry pipelines or build your own from 200+ connectors.
Live pipeline: data flows through each stage automatically
Connect APIs, databases and event streams. Orpheon validates schemas and normalizes inputs automatically.
Clean, enrich and reshape data with visual blocks or SQL/Python nodes for advanced workflows.
Run model training with tuned presets, experiment tracking and one-click retraining pipelines.
Deploy forecasts to production endpoints with monitoring, alerting and automatic drift handling.
A modular, container-native architecture that scales horizontally at every tier. Add replicas per workload — from plant-floor edge nodes to multi-GPU training clusters.
Raw → Bronze → Silver → Gold → Platinum — each layer adds quality, structure, and trust to your data.
Click to add replicas. Every tier scales independently, from edge ingest to GPU-accelerated training.
Every workload runs in isolated Docker containers orchestrated by Kubernetes with auto-healing and rolling updates.
Every layer of the stack is chosen for throughput, reliability, and developer experience — from edge protocols to GPU-accelerated ML.
Quantified savings per use case based on real deployments and customer benchmarks.
Purpose-built for industrial time-series workloads — not a general-purpose data lake with ML bolted on.
| Feature | NexPatch | Databricks | Snowflake | AWS IoT + SageMaker | Azure IoT + Synapse |
|---|---|---|---|---|---|
| Native IoT / time-series | ✓ | Partial | ✗ | Partial | Partial |
| Real-time streaming ETL | ✓ | ✓ | ✗ | ✓ | ✓ |
| Visual Pipeline Studio | ✓ | ✗ | ✗ | ✗ | Partial |
| Industry templates | ✓ | ✗ | ✗ | ✗ | ✗ |
| Edge-to-cloud sync | ✓ | ✗ | ✗ | Partial | Partial |
| Integrated ML training | ✓ | ✓ | Partial | ✓ | ✓ |
| Full on-prem deploy | ✓ | ✗ | ✗ | ✗ | Partial |
| Medallion architecture | ✓ | ✓ | Partial | ✗ | ✗ |
| Time-to-production | Hours | Weeks | Weeks | Months | Months |
| Annual cost (enterprise) | €48K | €120K+ | €90K+ | €150K+ | €130K+ |
Comparison based on publicly available documentation as of 2025. Your mileage may vary.
Last reviewed: May 2026.
Book a 30-minute demo to see Orpheon running on your industry's data. No commitment, no sales pressure.
In 30 minutes, we map which pipeline and forecasting approach fits your data sources, latency needs, and deployment constraints.