Enables generative and agentic AI capabilities across Siemens EDA tools, giving the user a context-aware natural language interface to operate across the entire EDA workflow.
Utilizes a family of specialized parsers to ingest and vectorize various EDA formats and data to foster a strong data flywheel effect and break silos across design teams.
Utilizes advanced retrieval augmented generation (RAG) framework to quickly and accurately answer your queries related to Siemens EDA tools, syntax and workflows.
Offers advanced custom access mapping and controls for secure RAG in addition to both on-premises and cloud deployment options without the need for third-party computing resources.
Accelerates designer productivity by automating routine tasks, analyzing EDA results and offering AI-powered debugging assistance, all accessible through natural language commands.
Supports multiple best-in-class LLMs for high-quality results, while enabling users to incorporate custom EDA data and create tailored workflows for their specific design needs.
Purpose-built for semiconductor and PCB design environments, this innovative solution delivers secure generative and agentic AI capabilities with unparalleled customization flexibility, seamlessly integrating across the entire EDA workflow.
Aprisa - 10x productivity boost, 3x compute-time efficiency, and 10% better PPA
Questa - 3x reduction in verification coverage closure time and 10x reduction in the verification of design changes
Solido - 2-1000X+ faster simulation and analysis
Tessent - 10x faster architecture implementation and 5x shorter test time for DFT
Veloce - 50% reduction in RTL compile time and 100% increase in throughput
Aprisa - Reduced floorplanning cycle time from ~3 to 4 weeks to 1 day with 17% improvement in wire length and 13% improvement in TNS
Calibre design - 60-400% runtime improvement for reliability checking with ML-optimized resource distribution
Calibre manufacturing - 2-4X runtime improvement in mask synthesis
Tessent - 2.5% yield improvement above entitlement ($M savings)