Infrastructure for next-generation compute

The control layer for analog and biological computing

Analog systems promise transformative efficiency gains. They remain confined to labs because you cannot scale what you cannot trust. Zeden builds the software that makes them reliable.

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GPU scaling is slowing. Data centers consume enormous energy. Demands from AI, simulation, and real-time processing grow exponentially.

Analog systems like neuromorphic, biological, memristor, and photonic computing offer 100 to 1000x efficiency gains. After billions invested globally, they remain confined to research environments.

The reason is simple: analog computing is inherently variable. The same inputs produce different outputs. Errors compound across networks. Without verification, there is no trust. Without trust, there is no deployment.

100x
Potential efficiency gains from analog substrates
B+
Invested globally in analog compute R&D
Lab
Where analog systems remain today
Trust
The missing layer between research and deployment
Three product lines, one thesis
Every product addresses the same core problem: making non-traditional compute substrates reliable enough to deploy.
BN

BitNexus

Software platform that optimizes numerical workloads across scientific simulation, ML inference, and signal processing on GPU hardware.

  • GPU-accelerated compute optimization
  • LLM inference with custom quantization
  • Portable binary format
  • Rust and CUDA backend
BC

Biological computing

Control and integration software for biological processing units where living neural tissue performs learning and inference alongside silicon.

  • Discrete state control architecture
  • Training protocol management
  • Hybrid bio-silicon integration
  • Partnered with tissue engineering team
AV

Analog vision

Bio-inspired analog vision processing for real-time motion and proximity detection at ultra-low power.

  • Modular sensor architecture
  • Multi-feature extraction pipeline
  • Ultra-low power analog operation
  • Hybrid analog-digital processing
Trust through verification
Analog substrates require a fundamentally different control paradigm than digital systems.

Signal verification

Real-time methods ensuring continuous substrate signals produce intended computational results. Applicable across biological, photonic, and memristor systems.

State control

Active intervention and correction for substrate drift, noise, and failure modes. Maintains computational integrity across extended operation periods.

Universal interface

Standardized protocols that abstract away substrate-specific complexities. Applications treat different analog substrates as interchangeable compute resources.

Intellectual property

Multiple provisional patents filed covering discrete state control, compute architectures, wave simulation methods, and analog sensor systems. Portfolio spans biological computing, numerical optimization, and analog hardware.

Federal R&D

Actively pursuing federal research and development contracts in biological computing and advanced compute architectures. Partnered with domain experts in tissue engineering, neuroscience, and defense technology.

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Interested in partnering or learning more about what we're building.

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