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Voice AI development services

Voice AI development & deployment for robots

We're the engineering partner that builds your robot's voice brain — custom on-device speech recognition, wake words, TTS and multi-turn dialogue — and ships it running on your edge silicon. Ultra-low latency, 100% offline.

Start a pilot How it works

What we build

Voice model customization

Bespoke acoustic models, custom wake words and branded TTS voices, tuned to your robot's persona and its real acoustic environment.

Dialogue logic architecture

Multi-turn behavioral state machines with intent recognition and context awareness — natural conversation, not a brittle command parser.

On-device deployment

We quantize, prune and compile your models to run 100% offline on Jetson, Rockchip, Qualcomm or custom NPUs — within your latency and power budget.

Full-stack integration

We port our voice middleware directly into your hardware's OS and software stack. You get a working voice brain, not a generic API.

On-device voice interaction pipeline from wake word through ASR, NLU and dialogue to TTSedge device · 100% offlineWake wordalways-onASRspeech→textNLUintentDialoguelogic / stateTTStext→speech
Figure: the on-device voice interaction pipeline — wake word, ASR (speech-to-text), NLU/intent, dialogue logic and TTS all run on the robot's edge silicon, with no cloud round-trip.

How it works

01

Scope & spec

We map your robot, languages, acoustic environment and constraints into a concrete deployment plan.

02

Model build / port

Train or adapt ASR, wake-word, TTS and dialogue models for your use case and target silicon.

03

Quantize & deploy

INT8 quantization, pruning and compilation (TensorRT / RKNN / SNPE) to hit your latency and power targets on-device.

04

Integrate & ship

We wire it into your stack, tune it in your real environment, and hand over a maintainable voice system.

Edge deployment pipeline: quantize to INT8, prune, compile and deploy to edge siliconbuild → deployModelFP32QuantizeINT8PrunesparsifyCompileTensorRT/RKNNEdge siliconJetson·RK3588
Figure: deploying a voice model to the edge — quantize to INT8, prune, compile with TensorRT / RKNN / SNPE, and run fully offline on NVIDIA Jetson, Rockchip or Qualcomm silicon.

Runs on your edge silicon

NVIDIA Jetson
NVIDIA JetsonOrin / Nano · TensorRT
Qualcomm
QualcommRobotics RB5 · SNPE
Rockchip
RockchipRK3588 / RV1126 · RKNN
Edge TPU / NPU
Edge TPU / NPUTFLite / ONNX Runtime

Frequently asked questions

Does the voice stack really run fully offline?
Yes. ASR, wake word, TTS and dialogue all run on the robot's silicon with no cloud round-trip. An optional cloud fallback is available only if you want it.
Which edge hardware do you support?
NVIDIA Jetson (Orin/Nano), Qualcomm Robotics (RB5), Rockchip (RK3588/RV1126), Google Edge TPU, and custom NPUs — via TensorRT, RKNN, SNPE, TFLite or ONNX Runtime.
What languages and wake words can you do?
Custom wake words and multi-language ASR/TTS, tuned for your target locales and your robot's acoustic environment (noise, distance, reverberation).
How do we start?
Send us your robot, target silicon and requirements via the form below. We'll come back with a tailored plan, usually within two business days.

Tell us about your robot

Send your robot, target silicon and requirements — we'll come back with a tailored plan, usually within two business days. Or email kaixinshier@gmail.com.