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AI Solutions for 1–10MB SRAM Edge SoCs
Enabling efficient edge AI for billions of devices. Our end-to-end platform optimizes, compiles, and deploys neural networks on ultra-constrained microcontrollers — delivering intelligence where it matters most.
Quantization · Pruning · Knowledge Distillation
Graph & Memory Optimization
On-Device Inference Engine
Low Power AI Silicon
Our three-tier platform takes your trained models from the cloud all the way down to silicon — automatically optimizing for the tightest memory and power budgets on the planet.
INT4/INT8 quantization, structured pruning, and knowledge distillation — shrink models up to 10× without meaningful accuracy loss.
Graph fusion, operator scheduling, and memory planning optimized for SRAM-only architectures with zero external memory access.
Lightweight inference engine under 50KB, designed for bare-metal and RTOS environments on Cortex-M and RISC-V cores.
From smart homes to industrial floors, our platform powers AI inference across the most demanding edge environments.
Always-on voice, gesture, and presence detection for connected home ecosystems.
On-device person & object detection with privacy-first edge processing.
Vibration analysis, quality inspection, and sensor fusion at the factory edge.
Real-time object classification and tracking in sub-mW power budgets.
Frame-level inference for counting, heatmaps, and behavioral analysis.
Keyword spotting and command recognition with <200KB model footprint.
Unsupervised edge learning for predictive alerts and fault identification.
Continuous equipment health monitoring with on-device trend analysis.
Every layer of our stack is purpose-built for ultra-low-power, SRAM-only edge silicon.
Hardware-aware NAS that co-optimizes accuracy and latency for your specific target silicon, finding Pareto-optimal model architectures automatically.
Per-layer sensitivity analysis for INT4/INT8 mixed precision — maximizing compression while preserving accuracy on critical operations.
Advanced operator fusion, memory reuse scheduling, and tiling strategies that fit complex networks into single-digit MB SRAM budgets.
Bare-metal inference engine with zero dynamic allocation, deterministic latency, and optimized SIMD kernels for Cortex-M and RISC-V.
Plug-in backend system supporting custom accelerator ISAs, enabling seamless deployment across diverse edge silicon platforms.
Cycle-accurate performance simulation, layer-by-layer memory maps, and power estimation before committing to silicon tape-out.
Let's explore how Qoresic can power your next-generation edge products with efficient, on-device intelligence.
Scan the QR code to connect via your preferred platform: