Machine vision consulting and embedded vision advisory for a team bringing face biometrics into ticketing, access control, frictionless payment, and credentialing on real edge devices.
Anonymised client
The client is a global leader in face-recognition technology. Estigiti supported the embedded and mobile side of that portfolio, especially where on-device CV/ML pipelines had to hold up across more than one runtime and hardware environment.
The work covered a broad delivery surface: software development, DevOps, verification QA, technical product management, and data collection support. The operational goal was to keep the delivery backbone credible across multiple embedded and mobile targets over time.
Keeping biometric pipelines consistent across many platforms, handling structured-light anti-spoofing, validating performance in hardware-in-the-loop, and supporting downstream customer integrations without fragmenting the engineering effort.
Estigiti operated as a managed team embedded into the client’s broader product effort. That team covered embedded software, mobile delivery, CI/CD, QA, data-support tooling, and technical product leadership. On the device side, the work ran across Ambarella CVflow, Rockchip RKNN, Hailo, Qualcomm QNN, iOS CoreML, and Android TFLite.
The service also included bespoke embedded software, structured IR-light processing, test infrastructure, and cloud/backend integration.
If your model works in isolation but not yet across the real device landscape, we can help with the runtime, pipeline, and delivery layers that make deployment stick.