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Cognichip Tech Stack
AI-powered chip design platform using physics-informed foundation models
Cognichip is building an AI system designed specifically for semiconductor design, grounded in physics-informed modeling rather than general-purpose LLMs. The tech stack reveals a company deeply embedded in hardware design workflows—Vivado, Vitis, Quartus, SystemVerilog, Verilog—paired with modern agentic AI infrastructure (LangGraph, LangChain, AutoGen, CrewAI). Hiring is heavily engineering-skewed (27 of 34 active roles), with 12 staff-level positions, signaling a focus on research and foundational AI systems rather than rapid customer acquisition.
Tech Stack 46 technologies
Core StackPython LangChain AWS GitHub Kubernetes Java Go TypeScript JavaScript React Redux Jenkins RAG Vivado Vitis Quartus SystemVerilog TCL UVM Verilog Verilator LangGraph AutoGen CrewAI FPGA LangSmith IAM Electron Visual Studio Code Zustand+16 more
What Cognichip Is Building
◆Challenges
- Adopting ai in silicon design workflows
- Curating massive hardware code datasets
- Cost efficiency
- Time-to-market acceleration
- Automating chip design
- Reducing manual verification effort
- Complex chip design workflows
- Agent performance optimization
- Production-grade agentic ai deployment
- Reliable production deployment of agentic ai systems
▲Active Projects
- Develop agentic ai systems for rtl generation
- Create libraries, tools, and benchmarks to increase design velocity
- Novel chip design methodologies
- Evaluation pipeline development for agentic systems
- Vs code-based ide development
- Ai-assisted coding features
- Agentic ai workflows
- Massive datasets of hardware code for model robustness
- Data generation for chip-design tasks
- Chip design workflow improvement system
Hiring Activity
35 roles · 25 in 30d
Department
Seniority
Company intelligence
