AI-Enabled Device Validation
Ship intelligent hardware faster: quantifiable AI validation, sensor fusion, and real-world testing for AI-enabled devices.
Request a QuoteQuantifiable Validation for AI-Enabled Products
AI hardware rarely fails because of the model; it fails under load, latency, noisy sensors, and real-world conditions. Novus pairs AI engineering with deep hardware and systems knowledge to prove how an intelligent device actually behaves once it ships.
We measure the things that matter for production: intent-recognition fidelity, response accuracy and F1 score, sensor signal integrity, and the CPU, memory, thermal, and battery cost of running AI alongside everything else the device does.
- Intent-recognition & accuracy (F1) validation
- Sensor fusion & signal integrity
- On-device, edge, and cloud AI
- System-resource impact (CPU/memory/thermal/battery)
- Real-world behavior under load
Capabilities Behind the Solution
AI engineering, sensor expertise, and the software to validate intelligent devices end-to-end.
- Edge / gateway / cloud AI
- Model tuning & deployment
- AI quality validation
- Sensor signal integrity
- Fusion algorithm validation
- Multi-modal data
- Test data generation
- Automation frameworks
- Results & metrics
Prove It Before Customers Do
We set measurable quality targets, validate against them, and confirm the device holds up in the real world.
- Accuracy & F1 goals
- Latency budgets
- Resource limits
- Intent & accuracy testing
- Sensor & fusion checks
- System-resource impact
- Test-home validation
- Noise & interference
- Edge-case behavior
Ready to Ship AI That Works in the Real World?
Talk to a Novus engineer about validating your AI-enabled device: accuracy, sensors, resources, and real-world behavior.