TRUSTED BY LEADING ORGANIZATIONS
Real Numbers, Real Deployments
125
X
Faster Inference
MODEL
HTCNN
DEPLOYMENT
STM32H747 MCU
RESULT
300s → 2.4s inference time
70
%
Memory Reduction
MODEL
Solar-31B / Multiple CV models
DEPLOYMENT
LPU / Server · NPU
RESULT
61.8 GB → ~19 GB / 60%+ size reduction
50
%
Inference Cost Reduction
MODEL
MoE LLM (Solar, Qwen3)
DEPLOYMENT
GPU Server (A100)
RESULT
GPU 4 → 2 units required
Solve Every Deployment Challenge
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PROFESSIONAL SERVICE
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When optimization becomes complex, our team ensures your models run successfully on your target device.
Edge AI Optimization
Expert-led model compression and hardware adaptation for edge devices including MCUs, mobile SoCs, and embedded platforms.
NPU Optimization
Deep compatibility work to make vision models and LLMs run on diverse NPU architectures with validated performance guarantees.
LLM Optimization
Specialize large language models for production — reduce GPU footprint, accelerate token throughput, and cut operational costs.
