01
Simulation Cost
Corner-heavy characterization and Monte Carlo runs consume weeks of compute and engineering time.
Intelligence for SRAM engineering
AI-Driven SRAM DTCO Workbench
Connect simulation, silicon and intelligence into one engineering workflow.
Purpose-built for SRAM
Explainable by design
TCADDevice physics
SPICECircuit behavior
Monte CarloVariation space
AIEngineering insight
DTCO ReportDecisions
Model insightVmin sensitivity isolated
96.4%01 / THE CHALLENGE
SRAM development is becoming increasingly complex.
More corners, more data and tighter margins make every design cycle harder to understand and optimize.
02
Data Fragmentation
TCAD, SPICE, silicon and lab data stay scattered across tools, formats and teams.
03
Engineering Knowledge
Critical debug knowledge remains trapped in scripts, reports and expert memory.
04
Silicon Learning
Measured-silicon lessons arrive late and rarely flow back into the next design cycle.
02 / THE WORKFLOW
One platform. Complete DTCO workflow.
Turn every experiment into reusable engineering intelligence—from raw simulation to explainable optimization.
01SimulationTCAD · SPICE
02DataUnified layer
03AI ModelsPredictive
04Root CauseExplainable
05OptimizationDesign space
06DTCO ReportTraceable
03 / CORE CAPABILITIES
Intelligence across the engineering loop.
A modular workbench that helps SRAM teams organize evidence, learn faster and make defensible design decisions.
Simulation Data Parser
Normalize TCAD, SPICE, Monte Carlo and silicon results into one engineering-ready data layer.
Surrogate Modeling
Build fast predictive models for the behaviors SRAM engineers care about.
Active Learning DOE
Select the most informative simulations and reduce iteration cost.
Root Cause Analysis
Expose the drivers, interactions and sensitivities behind failures.
Yield & Vmin Projection
Project distribution tails and operating margin across design and process conditions.
Automated DTCO Reports
Generate traceable findings, comparisons and engineering recommendations.
04 / PLATFORM
From EDA data to engineering decisions.
Gnozis connects the tools you already use with a shared data, intelligence and knowledge layer built for SRAM DTCO.
Closed-loop by designSimulation and silicon evidence continuously improve the next decision.
01EDA Tools
TCADSPICEMonte CarloSilicon Data
02Data Layer
ParsingNormalizationFeatures
03AI Layer
SurrogatesActive LearningExplainability
04Engineering Knowledge
ProcessDeviceCellCircuit
05Applications
OptimizationYield / VminDTCO Reports
05 / WHY GNOZIS
Built for the way SRAM engineers work.
SRAM Native
Designed around cells, arrays, variation, yield and Vmin—not generic analytics.
AI First
Intelligence is embedded across DOE, modeling, diagnosis and optimization.
Explainable
Every recommendation stays connected to evidence engineers can inspect.
Private Deployment
Keep proprietary PDK, design and silicon data inside your controlled environment.
06 / OUR VISION
Building the intelligence layer for silicon.
A continuously learning engineering system where every simulation and silicon measurement makes the next decision faster, clearer and more confident.
Accelerating SRAM innovation with AI.
07 / START A CONVERSATION
Ready to build the future of SRAM?
Bring your hardest SRAM DTCO workflow. We’ll show how Gnozis connects your data, models and engineering decisions.
hello@gnozis.cn