AI-Powered Chip Design Automation — Spec to Silicon
Qoresic orchestrates 19+ specialized AI agents across 24 EDA tool categories to autonomously design, verify, and optimize integrated circuits — from natural-language specification to manufacturable GDSII.
Pioneering the future of autonomous silicon intelligence, cognitive semiconductor infrastructure, and next-generation AI computing systems.
Founded by veteran semiconductor, EDA, and AI experts from Silicon Valley and Europe, Qoresic combines more than 25 years of deep industry experience across IC design, semiconductor engineering, EDA platforms, mathematical modeling, machine learning, AI algorithms, and advanced compute architectures.
The company was co-founded by a Silicon Valley semiconductor and EDA expert serving as Chief Meta Officer, together with a European AI scientist and mathematician serving as Chief AI Officer. The founding team brings decades of expertise spanning semiconductor physics, chip architecture, physical implementation, verification, optimization, AI infrastructure, and autonomous reasoning systems.
Qoresic's mission is to transform the semiconductor industry from fragmented tool-centric workflows into continuously learning, AI-native autonomous semiconductor intelligence ecosystems.
Autonomous orchestration for semiconductor development through multi-agent AI systems, reasoning engines, semiconductor memory infrastructure, and continuous silicon learning.
Next-generation Edge AGI silicon architectures designed for adaptive intelligence, distributed AI systems, and future autonomous computing — targeting robotics, industrial AI, autonomous machines, edge datacenters, and cognitive infrastructure platforms.
Advanced semiconductor modeling, AI-assisted IC design, and expert engineering services combining deep semiconductor knowledge with AI-driven engineering workflows for faster, smarter, and more adaptive silicon development.
A continuous silicon learning infrastructure connecting semiconductor lifecycle data into self-improving AI intelligence systems — creating continuously evolving ecosystems capable of adaptive optimization across the entire silicon lifecycle.
Qoresic believes the future of semiconductors will not be defined solely by transistor scaling, but by cognitive infrastructure — systems capable of reasoning, learning, adapting, and continuously optimizing across silicon, software, packaging, systems, and datacenter infrastructure.
The future is not only electronic.
It is intelligent.
It is autonomous.
It is Qoresic.
The Qoresic AI Supervisor Brain orchestrates specialized agents across every stage of IC design — from specification through tape-out — with persistent engineering memory that learns from every project.
SRAM-native dataflow architectures and Z-axis stacking for adaptive intelligence at the edge.
SRAM-native dataflow NPU chip with 1–2GB on-chip SRAM, 16–32 INT4 Tensor Cores, Cortex-A78AE + A55, TEE security, and full-featured IO for autonomous edge AI appliances.
Z-axis SRAM stacking via SoIC hybrid bonding — moves cache out of the XY logic plane into vertical layers above the compute die. Frees 60% die area for tensor cores.
Practical deployment pipelines from model compression to encrypted on-device inference.
End-to-end three-tier stack for deploying neural networks on 1–10MB SRAM microcontrollers: Model Optimizer → AI Compiler → sub-50KB Edge Runtime. Targets Cortex-M and RISC-V.
Closed-loop chip design from natural-language specification to manufacturable GDSII. Multi-candidate RTL generation, SVA + testbench co-gen, PPA scoring & self-refinement loop.
Centered Binomial Noise framework for Fully Homomorphic Encryption on sub-1W edge devices. 4× latency and power reduction vs. Gaussian baseline.
From agentic physical design at advanced nodes to a fully autonomous semiconductor operating system.
Unlike stateless AI, Qoresic builds a "Persistent Engineering Memory" that accumulates organizational knowledge across every tape-out. 8 specialized agents collaborate for timing closure, IR drop, ECO convergence, and signoff correlation.
| Current Demo | N7 production-style implementation baseline |
| Next Phase | N6+ parallel implementation intelligence |
| Roadmap End | N1+ autonomous engineering intelligence |
| Key Moat | Cross-project silicon learning flywheel |
Reframes semiconductor development from "Human → Tool → Result" to "Goal → AI Reasoning → Autonomous Orchestration → Continuous Learning." EDA tools become execution engines; AI agents become design intelligence.
| Today | AI agents augment engineers; humans drive flow |
| Near-term | AI Brain takes execution, humans approve gates |
| Future | NL product intent → autonomous silicon to manufacture |
| Long-term | Self-improving silicon across chip generations |
Let's explore how Qoresic can accelerate your semiconductor development with autonomous AI-driven design, verification, and deployment.
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