We work with teams deploying AI models on constrained edge hardware — from proof-of-concept to production. Real silicon, real constraints, real timelines.
We take your existing model and deploy it to your target hardware — handling format conversion, graph optimisation, and backend selection so you can focus on the application.
Full integration of the Nuatara engine into your product — hardware abstraction, unified API, and multi-target support across your silicon fleet. Production-grade from day one.
Already building an edge AI pipeline? We review your model, precision strategy, runtime choices, and BSP dependencies — with prioritised, actionable recommendations.
We embed with your team and validate on your actual target hardware — not a simulator, not an emulator.
We review your model, target silicon, and deployment constraints in a one-hour call.
We run your model on your hardware and give you real performance numbers — throughput, latency, accuracy.
Engine integration, graph optimisation, and API wiring — in focused two-week cycles on your actual board.
Full documentation, CI pipeline, and handover to your engineering team.
Our team brings expertise that goes deeper than AI deployment. If your project touches any of the areas below, reach out — we can help.
Bare-metal bring-up, RTOS integration, memory-constrained environments, and hardware/software co-design for edge devices.
Image signal processing pipeline design — from sensor RAW through demosaicing, noise reduction, and colour science for machine vision.
Real-time video encode/decode, latency-optimised pipelines, and integration of hardware video accelerators on embedded SoCs.
Serialiser/Deserialiser design and bring-up for camera links, MIPI, and high-speed sensor interfaces in industrial and automotive contexts.
Talk to us about your target silicon, your model, and your deployment constraints.
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