Qoresic is an AI-native semiconductor technology company advancing the frontier of autonomous silicon intelligence, cognitive semiconductor infrastructure, and next-generation AI computing systems.
Founded by veteran semiconductor, EDA, and AI specialists from Silicon Valley and Europe, Qoresic brings together more than 25 years of combined industry experience spanning IC design, semiconductor engineering, EDA platforms, mathematical modeling, machine learning, AI algorithms, and advanced compute architectures.
Qoresic's platform is architected not as a point tool, but as a complete AI-native engineering organization — a coordinated system of specialized agents, deterministic engineering tools, and human sign-off authority spanning the entire semiconductor value chain, now extended into the enterprise systems that surround it.
Transform the semiconductor industry from fragmented, tool-centric workflows into continuously learning, AI-native autonomous intelligence ecosystems.
A future where silicon, software, packaging, systems, and the enterprises that run them are cognitive infrastructure — reasoning, learning, and continuously optimizing together.
Qoresic's agents are not isolated copilots or single-turn demonstrations. Across all ten product lines, they operate as a virtual workforce — with defined roles, reporting lines, review authority, and sign-off — governed the same way a professional engineering and operations organization holds itself accountable.
Each agent operates under a delegated identity, never impersonation — every action is traceable to the human or system that authorized it.
AI-proposed candidates and transactions are routed to named human engineers or business owners for sign-off — never self-approved.
Every decision, tool invocation, and data lineage is captured in an immutable audit trail, held to the same standard as a regulated organization's human staff.
Deterministic tools and rules — not the agent itself — serve as the sole arbiter of pass, fail, correctness, and compliance.
Spanning the full semiconductor lifecycle and into enterprise operations. Each product line runs on the shared control-plane architecture, with its own domain knowledge layer, execution toolchain, and quality gates.
Addresses the core analog design challenge: whether a circuit continues to meet specification and yield targets under process, voltage, temperature, load, parasitic, and mismatch uncertainty — not merely whether the code compiles. Exploration and verification are strictly separated, with verification conditions and pass/fail rules held read-only so no agent can cause a design to merely appear compliant.
Spans front-end (RTL, verification, synthesis), DFT, and back-end (place-and-route, sign-off) to determine whether functionality is correct, timing converges, and yield is manufacturable. Managed as a stateful task graph rather than a single-turn exchange, since a single design task may run for hours or days.
Co-verifies hardware and firmware in tandem — CPU core, system bus, memory, peripherals, low-power modes, and security — since any hardware change can compromise firmware compatibility, and any firmware assumption must be validated against actual register behavior.
Centers on bitcell stability, read/write margin, yield, and reliability, producing compiler IP (Liberty/LEF/RTL models) ready for downstream SoC integration. Because memory metrics are inherently statistical — offset, yield, mismatch — a favorable average is insufficient; tail behavior must be explicitly validated.
Covers diodes, MOSFETs, IGBTs, SiC, and GaN devices, where the central challenge is co-optimizing device physics with thermo-mechanical packaging rather than circuit topology. TCAD serves as the central arbiter, with every geometric and process assumption calibrated against wafer measurement.
Jointly simulates optical behavior (wavelength, mode, coupling) and electrical behavior (carrier transport, gain), extending to package-level fiber alignment. Yield depends as much on packaging alignment precision and material index uniformity as on electrical performance.
Spans three carrier types — PCB (board-level), SiP (multi-die package integration), and WLP (wafer-level packaging) — converging electrical, thermal, mechanical, and manufacturing domains. Responsibility extends beyond chip design itself into OSAT, supply chain, and manufacturing yield.
Provides the physical simulation backbone shared by the AMS, ASIC, MCU, Memory, Discrete, and Optoelectronic product lines, predicting process and device behavior ahead of silicon and calibrating models against measurement. Subject to numerical-convergence and physical-plausibility quality gates not required elsewhere in the portfolio.
Operates between design sign-off and wafer exposure, applying optical proximity correction to derive mask geometry for a target exposure tool, light source, resist, and etch conditions. Judged directly against wafer measurement, with the deliverable being verifiable mask-data evidence rather than a modified GDS alone.
Distinct in nature from the nine silicon-design product lines above: this line reads, computes, drafts, and executes transactions across multi-tenant financial, HR, and supply-chain systems. Core risks are financial accuracy, privilege escalation, and segregation of duties — an LLM is never treated as the source of truth for ERP data, financial rules, transaction authority, or execution itself.
A growing library of live demonstrations across the Qoresic portfolio — from natural-language RTL generation to SAP-integrated enterprise automation.
Autonomous agents spanning RTL, physical design, analog IC, GDSII layout, and technical document intelligence.
Turns natural-language module descriptions into SystemVerilog RTL, testbenches, and a 6-axis quality score.
Watch Demo ›Live-streams verification logs and auto-applies fixes to reach 100% test pass rate and coverage.
Watch Demo ›Block-level SystemVerilog validation with real-time sync, targeting TSMC 12nm specifications.
Watch Demo ›Converts high-level synthesis goals into complete, validated synthesis TCL scripts.
Watch Demo ›Runs a Constraint → Score → Action → Report loop across timing, power, area, congestion and IR-drop.
Watch Demo ›Reads post-route reports and layout screenshots to diagnose violations and generate TCL fixes.
Watch Demo ›Uses NVIDIA Nemotron to rank timing-log root causes and recommend risk-rated fixes.
Watch Demo ›Converts plain-text floorplan intent into validated layouts and downloadable GDSII packages.
Watch Demo ›Runs a full RTL-to-sign-off flow with live thermal heatmap simulation.
Watch Demo ›Turns analog specs into design contracts, verified across 45 PVT corners.
Watch Demo ›Combines multi-corner SPICE sizing with multi-layer physical layout and GDSII output.
Watch Demo ›An engineering copilot that explains design constraints, benchmarks specs and proposes power-saving techniques.
Watch Demo ›Answers deep technical queries and writes Cadence Innovus floorplanning TCL code.
Watch Demo ›A 9-stage pipeline with strict pass/fail gates that rolls back rejected proposals automatically.
Watch Demo ›Monitors running EDA jobs and repairs timing violations in real time.
Watch Demo ›Renders interactive logic-gate schematics directly from netlists for human and AI review.
Watch Demo ›Cross-references datasheets and research papers, answering queries with page-cited excerpts.
Watch Demo ›The same trust architecture applied to enterprise operations — from executive assistants to SAP-integrated workflows.
Builds board reports from SAP, Salesforce and Confluence, and turns meetings into decisions and action items.
Watch Demo ›Verifies leave policy, routes approvals, and writes back to SAP ERP with a full audit trail.
Watch Demo ›The same CEO-office assistant working seamlessly across English, Chinese, Japanese and Korean.
Watch Demo ›Pulls wafer-lot data from SAP into vector and graph databases with live yield dashboards.
Watch Demo ›Turns plain-language integration intents into the right SOAP or OData API with payload skeletons.
Watch Demo ›Manages orders, materials and suppliers, and speeds up purchase-order creation.
Watch Demo ›Generates natural-language sales analytics while blocking unauthorized or destructive requests in real time.
Watch Demo ›Across all ten product lines, Qoresic is building a continuous learning infrastructure that converts lifecycle data into self-improving AI intelligence — creating an evolving intelligence ecosystem capable of adaptive optimization across the entire silicon lifecycle, and the business operations that surround it.
Qoresic believes the future of semiconductors will be defined not by transistor scaling alone, but by cognitive infrastructure — systems capable of reasoning, learning, adapting, and continuously optimizing across silicon, software, packaging, systems, datacenter infrastructure, and the enterprises that run them.
Autonomous Silicon Development — from analog IC to advanced packaging
AI-Native Semiconductor & Enterprise Infrastructure
Runtime Adaptive Computing
Semiconductor Cognitive Systems
Wafer-to-Datacenter-to-Enterprise Optimization
Physics-Native Compute Architectures of the Future
The future is not only electronic.
It is intelligent. It is autonomous.
It is Qoresic.
Partner with Qoresic for trustworthy, production-grade Agentic AI across your semiconductor and enterprise operations. Request a technical briefing or discuss a pilot engagement.
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